\bibitem{Salimi:IoTJ2022} M. Salimibeni, Z. Hajiakhondi-Meybodi, A. Mohammadi and Y. Wang, \newblock "TB-ICT: A Trustworthy Blockchain-Enabled System for Indoor Contact Tracing in Epidemic Control," \newblock {\em IEEE Internet of Things Journal, 2022}, doi: 10.1109/JIOT.2022.3223329. In Press. \bibitem{Salimi:Sensors2022} M. Salimibeni, P. Malekzadeh, A. Mohammadi and K.N. Plataniotis, \newblock "MAAKF-SR: Multi-Agent Adaptive Kalman Filtering-based Successor Representation," \newblock {\em Sensors,} vol. 22, no. 4, 2022. \bibitem{Salimi:APSIPA2023} M. Salimibeni, A. Mohammadi, Z. Hajiakhondi, M. Atashi, P. Malekzadeh, and K.N. Plataniotis, \newblock "Reinforcement Learning-based Information Fusion for Multiple Model BLE-based Indoor Localization/Tracking," \newblock {\em Submitted to APSIPA Trans. on Signal and Information Processing (ATSIP)}, 2023. \bibitem{Salimi:ICASSP2023} M. Salimibeni, A. Mohammadi, N. Plataniotis, \newblock "RL-IFF: Reinforcement Learning based Information Fusion for Indoor Localization”," \newblock {\em Submitted to IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)}, 2023. \bibitem{Salimi:wfIOT} M. Salimibeni, Z. HajiAkhondi-Meybodi, A. Mohammadi, \newblock "TB-ICT: A Trustworthy Blockchain-Enabled System for Indoor Contact Tracing in Epidemic Control," \newblock {\em IEEE 8th World Forum on Internet of Things (WF-IoT)}, 2022. \bibitem{Salimi:Icassp} M. Salimibeni, P. Malekzadeh, A. Mohammadi, A. Assa and K. N. Plataniotis, \newblock "MAKF-SR: Multi- Agent Adaptive Kalman Filtering-based Successor Representations," \newblock {\em IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)}, 2021, pp. 8037-8041. \bibitem{Salimi:Eusipco} M. Salimibeni, M. Atashi, P. Malekzadeh, Z. HajiAkhondi-Meybodi, K. N. Plataniotis, A. Mohammadi, \newblock ``IoT-TD: IoT Dataset for Multiple Model BLE-based IndoorLocalization/Tracking,'' \newblock {\em 28th European Signal Processing Conference (EUSIPCO)}, 2020, pp. 1697-1701. \bibitem{Salimi:Asilomar} M. Salimibeni, P. Malekzadeh, A. Mohammadi and K. N. Plataniotis, \newblock ``Distributed Hybrid Kalman Temporal Differences for Reinforcement Learning,'' \newblock {\em IEEE International Asilomar Conference on Signals, Systems, and Computers}, 2020, pp. 579-583. \bibitem{Salimi:sensors2019} M. Salimibeni, P. Malekzadeh, M. Atashi, M. Barbulescu, K. N. Plataniotis and A. Mohammadi, \newblock ``Event-Triggered Monitoring/Communication of Inertial Measurement Unit for IoT Applications,'' \newblock {\em IEEE SENSORS}, 2019, pp. 1-4. \bibitem{Li:2020} Y. Li, X. Hu, Y. Zhuang, Z. Gao, P. Zhang and N. El-Sheimy, \newblock "Deep Reinforcement Learning (DRL): Another Perspective for Unsupervised Wireless Localization," \newblock {\em IEEE Internet of Things Journal}, invol. 7, no. 7, pp. 6279-6287, July 2020. \bibitem{P. Silva} P. Silva, V. Kaseva, E. Lohan, \newblock "Wireless Positioning in IoT: A Look at Current \& Future Trends," \newblock {\em Sensors}, vol. 8, no. 8, 2018. \bibitem{Spachos:2020} P. Spachos and K. N. Plataniotis, \newblock "BLE Beacons for Indoor Positioning at an Interactive IoT-Based Smart Museum," \newblock {\em IEEE Systems Journal}, vol. 14, no. 3, pp. 3483-3493, Sept. 2020. \bibitem{Ng:2021} P. C. Ng, P. Spachos and K. N. Plataniotis, \newblock "COVID-19 and Your Smartphone: BLE-Based Smart Contact Tracing," \newblock {\em IEEE Systems Journal}, doi: 10.1109/JSYST.2021.3055675., 2021. \bibitem{Zafari:2017} F. Zafari, I. Papapanagiotou, M. Devetsikiotis, T.J. Hacker, \newblock ``An iBeacon based Proximity and Indoor Localization System,'' \newblock https://arxiv.org/abs/1703.07876, 2017. \bibitem{Dinh:2020} T. T. Dinh, N. Duong and K. Sandrasegaran, \newblock "Smartphone-Based Indoor Positioning Using BLE iBeacon and Reliable Lightweight Fingerprint Map," in IEEE Sensors Journal, vol. 20, no. 17, pp. 10283-10294, 1 Sept.1, 2020, doi: 10.1109/JSEN.2020.2989411. \bibitem{Zheng:2017} K. Zheng, \textit{et al.}, \newblock "Energy-Efficient Localization and Tracking of Mobile Devices in Wireless Sensor Networks," \newblock {\em IEEE Transactions on Vehicular Technology}, 2017. \bibitem{Davidson:2017} P. Davidson and R. Piche, \newblock "A Survey of Selected Indoor Positioning Methods for Smartphones," \newblock {\em IEEE Communications Surveys \& Tutorials}, vol. 19, no. 2, pp. 1347-1370, 2017. \bibitem{Hoang:2019} M. T. Hoang, B. Yuen, X. Dong, T. Lu, R. Westendorp and K. Reddy, \newblock "Recurrent Neural Networks for Accurate RSSI Indoor Localization," \newblock in IEEE Internet of Things Journal, vol. 6, no. 6, pp. 10639-10651, Dec. 2019, doi: 10.1109/JIOT.2019.2940368. \bibitem{Farahsari:2022} P. S. Farahsari, A. Farahzadi, J. Rezazadeh and A. Bagheri, \newblock ``A Survey on Indoor Positioning Systems for IoT-Based Applications,'' \newblock {\em IEEE Internet of Things Journal}, vol. 9, no. 10, pp. 7680-7699, 15 May15, 2022. \bibitem{Parvin:SPL} P. Malekzadeh, A. Mohammadi, M. Barbulescu, and K.N. Plataniotis, \newblock "STUPEFY: Set-Valued Box Particle Filtering for BLE-based Indoor Localization" \newblock {\em IEEE Signal Processing Letters}, 2019. In Press. \bibitem{Atashi:FUSION} M. Atashi, M. Salimibeni, P. Malekzadeh, M. Barbulescu, K. N. Plataniotis and A. Mohammadi, \newblock "Multiple Model BLE-based Tracking via Validation of RSSI Fluctuations under Different Conditions," \newblock {\em International Conference on Information Fusion (FUSION)}, Ottawa, ON, Canada, 2019, pp. 1-6. \bibitem{D.An} D. An and J. Lee, \newblock "Derivation of an Approximate Location Estimate in Angle-of-Arrival Based Localization in the Presence of Angle-of-Arrival Estimate Error and Sensor Location Error," \newblock {\em IEEE World Symposium on Communication Engineering (WSCE)}, 2018, pp. 1-5. \bibitem{Sark} V. Sark and E. Grass, \newblock "Modified Equivalent Time Sampling for Improving Precision of Time-of-Flight based Localization," \newblock {\em IEEE Annual International Symposium on Personal, Indoor, and Mobile Radio Communications (PIMRC)}, 2013, pp. 370-374. \bibitem{G. Fokin} G. Fokin, A. Kireev and A. H. A. Al-odhari, \newblock "TDOA Positioning Accuracy Performance Evaluation for ARC Sensor Configuration," \newblock {\em Systems of Signals Generating and Processing in the Field of on Board Communications}, 2018, pp. 1-5. \bibitem{Sadowski:2019} S. Sadowski and P. Spachos, \newblock ``Optimization of BLE Beacon Density for RSSI-Based Indoor Localization,'' 2019 IEEE \newblock {\em International Conference on Communications Workshops (ICC Workshops)}, Shanghai, China, 2019, pp. 1-6. \bibitem{Sadowski:2018} S. Sadowski and P. Spachos, \newblock ``RSSI-Based Indoor Localization With the Internet of Things,'' \newblock {\em IEEE Access}, vol. 6, pp. 30149-30161, 2018. \bibitem{Kumar} S. Kumar, R. Ramaswami, and K. Tomar, \newblock ``Localization in Wireless Sensor Networks using Directionally Information," \newblock {\em IEEE International Advance Computing Conference (IACC)}, 2013, pp. 577-582. \bibitem{Parvin:access} P. Malekzadeh, M. Salimibeni, A. Mohammadi, A. Assa and K. N. Plataniotis, \newblock "MM-KTD: Multiple Model Kalman Temporal Differences for Reinforcement Learning," \newblock{\em IEEE Access}, vol. 8, pp. 128716-128729, 2020. \bibitem{WLANbook} A. Kushki, K.N. Plataniotis and A.N. Venetsanopoulos \newblock ``WLAN Positioning Systems: Principles and Applications in Location-based Services,'' \newblock {\em Cambridge University Press}, 2012. \bibitem{C. Ranasinghe} C. Ranasinghe and C. Kray, \newblock ``Location Information Quality: A Review,'' \newblock {\em Sensors (Basel, Switzerland)}, 2018, 18(11), 3999. \bibitem{P. Jeongyeup} P. Jeongyeup, K. JeongGil, and S. Hyungsik, \newblock ``A Measurement Study of BLE iBeacon and Geometric Adjustment Scheme for Indoor Location-Based Mobile Applications,'' \newblock {\em Mobile Information Systems}, vol. 2016, Article ID 8367638, 13 pages. \bibitem{fingerprinting:2017} M.C. Cara, J.L. Melgarejo, G.B. Rocca, L.O. Barbosa and I.G. Varea, \newblock ``An analysis of multiple criteria and setups for Bluetooth smartphone-based indoor localization mechanism,'' \newblock {\em Journal of Sensors}, 2017. \bibitem{fingerprint_trilateration} YB. Bai, \textit{et al.}, \newblock ``A new method for improving Wi-Fi-based indoor positioning accuracy,'' \newblock {\em J. Location-based Services}, vol. 8, no. 3, pp. 135-147, 2014. \bibitem{Cho:ENC} S. Y. Cho and C. G. Park, \newblock ``Threshold-less Zero-Velocity Detection Algorithm for Pedestrian Dead Reckoning,'' \newblock {\em European Navigation Conference (ENC)}, Warsaw, Poland, 2019, pp. 1-5. \bibitem{Foxlin:PDR} E. Foxlin, \newblock ``Pedestrian tracking with shoe-mounted inertial sensors,'' \newblock {\em IEEE Computer Graphics and Applications}, vol. 25, no. 6, pp. 38-46, Nov.-Dec. 2005. \bibitem{Harle:Survey} R. Harle, \newblock ``A Survey of Indoor Inertial Positioning Systems for Pedestrians,'' \newblock {\em IEEE Communications Surveys and Tutorials}, vol. 15, no. 3, pp. 1281-1293, Third Quarter 2013. %%%%% \bibitem{Kang:Sensors} W. Kang and Y. Han, \newblock ``SmartPDR: Smartphone-Based Pedestrian Dead Reckoning for Indoor Localization,'' \newblock {\em IEEE Sensors Journal}, vol. 15, no. 5, pp. 2906-2916, May 2015. \bibitem{Monfared:2018} S. Monfared, T. Nguyen, L. Petrillo, P. De Doncker, and F. Horlin, \newblock ``Experimental Demonstration of BLE Transmitter Positioning Based on AOA Estimation,'' \newblock {\em IEEE International Symposium on Personal, Indoor and Mobile Radio Communications}, Bologna, Dec. 2018, pp. 856-859. \bibitem{Cominelli:2019} M. Cominelli, P Patras, and F Gringoli, \newblock ``Dead on Arrival: An Empirical Study of The Bluetooth 5.1 Positioning System,'' \newblock {\em International Workshop on Wireless Network Test beds, Experimental Evaluation and Characterization}, pp. 13-20. Oct. 2019. \bibitem{Hu:2019} P. Hu, Q. Bao and Z. Chen, \newblock ``Target Detection and Localization Using Non-Cooperative Frequency Agile Phased Array Radar Illuminator,'' \newblock {\em IEEE Access}, vol. 7, pp. 111277-111286, Aug. 2019. \bibitem{Zhou:2011} J. Zhou, H. Zhang and L. Mo, \newblock ``Two-dimension localization of passive RFID tags using AOA estimation,'' \newblock {\em IEEE International Instrumentation and Measurement Technology Conference}, May 2011, pp. 1-5. \bibitem{Zhang:2018} X. Zhang, W. Chen, W. Zheng, Z. Xia and Y. Wang, \newblock ``Localization of Near-Field Sources: A Reduced-Dimension MUSIC Algorithm,'' \newblock{ \em IEEE Communications Letters}, vol. 22, no. 7, pp. 1422-1425, Jul. 2018. \bibitem{Hossain:2017} M. D. Hossain and A. S. Mohan, \newblock ``Eigenspace Time-Reversal Robust Capon Beamforming for Target Localization in Continuous Random Media,'' \newblock{\em EEE Antennas and Wireless Propagation Letters}, vol. 16, pp. 1605-1608, Jan. 2017. \bibitem{Kulin:2018} M. Kulin, T. Kazaz, I. Moerman, and E. De Poorter, \newblock ``End-to-End Learning From Spectrum Data: A Deep Learning Approach for Wireless Signal Identification in Spectrum Monitoring Applications,'' \newblock {\em IEEE Access}, vol. 6, pp. 18484-18501, Mar. 2018. \bibitem{Hajiakhondi:2020_1} Z.~HajiAkhondi-Meybodi, M.~S.~Beni, K. N. Plataniotis, and A. Mohammadi \newblock ``Bluetooth Low Energy-based Angle of Arrival Estimation via Switch Antenna Array for Indoor Localization,'' \newblock {\em International Conference on Information Fusion}, July 2020. \bibitem{Hajiakhondi:2020_2} Z.~HajiAkhondi-Meybodi, M.~S.~Beni, A. Mohammadi, and K. N. Plataniotis, \newblock ``Bluetooth Low Energy-based Angle of Arrival Estimation in Presence of Rayleigh Fading,'' \newblock Accepted in {\em IEEE International Conference on Systems, Man, and Sybernetics}, 2020. \bibitem{Hajiakhondi:SMC2020} Z.~HajiAkhondi-Meybodi, M.~S.~Beni, A. Mohammadi, and K. N. Plataniotis, \newblock ``Bluetooth Low Energy-based Angle of Arrival Estimation in Presence of Rayleigh Fading,'' \newblock {\em IEEE International Conference on Systems, Man, and Sybernetics}, 2020. \bibitem{Wu:2019} K. Wu, W. Ni, T. Su, R. P. Liu and Y. J. Guo, \newblock ``Expeditious Estimation of Angle-of-Arrival for Hybrid Butler Matrix Arrays,'' \newblock {\em IEEE Transactions on Wireless Communications} vol. 18, no. 4, pp. 2170-2185, Apr. 2019. \bibitem{Nguyen:2019} N. H. Nguyen, and K. Dogancay, \newblock ``Closed-Form Algebraic Solutions for Angle-of-Arrival Source Localization With Bayesian Priors,'' \newblock {\em IEEE Transactions on Wireless Communications}, vol. 18, no. 8, May 2019, pp. 3827--3842. \bibitem{Cheng:2015} L. Cheng, Y. Wu, J. Zhang and L. Liu, ``Subspace Identification for DOA Estimation in Massive/Full-Dimension MIMO Systems: Bad Data Mitigation and Automatic Source Enumeration," \newblock {\em IEEE Transactions on Signal Processing}, vol. 63, no. 22, pp. 5897-5909, Nov. 2015. \bibitem{Shafin:2016} R. Shafin, L. Liu, J. Zhang and Y. Wu, ``DoA Estimation and Capacity Analysis for 3-D Millimeter Wave Massive-MIMO/FD-MIMO OFDM Systems," \newblock {\em IEEE Transactions on Wireless Communications}, vol. 15, no. 10, pp. 6963-6978, Oct. 2016. \bibitem{Yassin} A. Yassin, Y. Nasser, M. Awad, A. Al-Dubai, R. Liu, Ch. Yuen, R. Raulefs, and E. Aboutanios, ``Recent Advances in Indoor Localization: A Survey on Theoretical Approaches and Applications," \newblock {\em IEEE Commun. Surveys Tuts.}, vol. 19, no. 2, pp. 1327-1346, Secondquarter 2017. \bibitem{He:2014} J. He, Y. Geng, F. Liu and C. Xu, ``CC-KF: Enhanced TOA Performance in Multipath and NLOS Indoor Extreme Environment," \newblock {\em EEE Sensors Journal}, vol. 14, no. 11, pp. 3766-3774, Nov. 2014. \bibitem{Zhang:2016} C. Zhang, X. Bao, Q. Wei, Q. Ma, Y. Yang, and Q. Wang, ``A Kalman filter for UWB positioning in LOS/NLOS scenarios," \newblock {\em in Proc. International Conference on Ubiquitous Positioning, Indoor Navigation and Location Based Services}, Nov. 2016, pp. 73-78. \bibitem{Exel:2014} R. Exel and T. Bigler, ``ToA ranging using subsample peak estimation and equalizer-based multipath reduction," \newblock {\em in Proc. IEEE Wireless Communications and Networking Conference (WCNC)}, Istanbul, Apr. 2014, pp. 2964-2969. \bibitem{Wang2017} X. Wang, X. Wang, and S. Mao. \newblock``CiFi: Deep convolutional neural networks for indoor localization with 5 GHz Wi-Fi," \newblock {\em IEEE International Conference on Communications (ICC)}, pp. 1-6, May 2017. \bibitem{Wang2018} X. Wang, X. Wang and S. Mao, \newblock``Deep Convolutional Neural Networks for Indoor Localization with CSI Images," \newblock {\em IEEE Trans. Netw. Sci. Eng.}, vol. 7, no. 1, pp. 316-327, Mar. 2020. \bibitem{Comiter:2018} M. Comiter, and H. T. Kung, \newblock``Localization Convolutional Neural Networks Using Angle of Arrival Images," \newblock {\em in Proc. IEEE Global Communications Conference}, Abu Dhabi, Dec. 2018, pp. 1-7. \bibitem{Khan:2019} A. Khan, S. Wang and Z. Zhu, ``Angle-of-Arrival Estimation Using an Adaptive Machine Learning Framework," \newblock {\em IEEE Communications Letters}, vol. 23, no. 2, pp. 294-297, Feb. 2019. \bibitem{Hsieh:2019} C. Hsieh, J. Chen and B. Nien, \newblock``Deep Learning-Based Indoor Localization Using Received Signal Strength and Channel State Information," \newblock {\em IEEE Access}, vol. 7, pp. 33256-33267, 2019. \bibitem{Ferrag2021} M. A. Ferrag, L. Shu and K. -K. R. Choo, \newblock ``Fighting COVID-19 and Future Pandemics With the Internet of Things: Security and Privacy Perspectives," \newblock{ \em IEEE/CAA Journal of Automatica Sinica}, vol. 8, no. 9, pp. 1477-1499, September 2021. %=================== % Literature Review - Prominant Contact Tracing (CT) applications %=================== \bibitem{Bay:2020} J. Bay, J. Kek, A. Tan, C. S. Hau, L. Yongquan, and J. Tan, T. A. Quy, \newblock ``BlueTrace: A privacy-preserving protocol for communitydriven contact tracing across borders,” \newblock {\em Singapores Government Technology Agency}, Singapore, White Paper, p. 9, 2020. \bibitem{Harvard2020} \newblock ``Harvard College. Surveys, app. to track COVID-19," \newblock Available: https://www.hsph.harvard.edu/coronavirus/covid-19-response-public-health-in-action/surveys-apps-to-track-covid-19/, Acc. on: Dec. 27, 2020. \bibitem{Apple:2020} \newblock ``Exposure Notification,” Apple Inc., Cupertino, CA, USA and Google LLC., Mountain View, CA, USA, May 2020. \bibitem{Levy:2020} I. Levy, \newblock ``The Security Behind the NHS Contact Tracing App,” Accessed: May 8, 2020. [Online]. Available: https://www.ncsc.gov.uk/blog-post/security-behind-nhs-contact-tracing-app. \bibitem{Mozur:2020} P. Mozur, R. Zhong, and A. Krolik, \newblock ``In Coronavirus Fight, China Gives Citizens a Color Code, With Red Flags,” New York, NY, USA, 2020. [Online]. Available: https://www.nytimes.com/2020/03/01/business/china-coronavirus-surveillance.html. \bibitem{Ahmed:2020} N. Ahmed, R. A. Michelin, W. Xue, S. Ruj, R. Malaney, S. S.Kanhere, A. Seneviratne, W. Hu, H. Janicke, and S. K. Jha, \newblock ``A Survey of COVID-19 Contact Tracing Apps,” \newblock {\em IEEE Access}, vol. 8, pp. 134 577–134 601, 2020. \bibitem{Zhu:2021} L. Zhu, X. Tang, M. Shen, F. Gao, J. Zhang and X. Du, \newblock ``Privacy-Preserving ML Training in IoT Aggregation Scenarios,” \newblock {\em IEEE Internet of Things Journal}, vol. 8, no. 15, pp. 12106-12118, Aug, 2021. \bibitem{Vaudenay:2020} S. Vaudenay, \newblock ``Centralized or decentralized? the contact tracing dilemma,” \newblock {\em TIACR Cryptol}, ePrint Arch., vol. 2020, p. 531, 2020. \bibitem{Beskorovajnov:2020} W. Beskorovajnov, F. Dörre, G. Hartung, \textit{et al.}, \newblock ``Contra corona: Contact tracing against the coronavirus by bridging the centralized–decentralized divide for stronger privacy,” \newblock {\em Crypt. ePrint Archive}, Report 2020/505, 2020. \bibitem{Islam2022} A. Islam, A. Al Amin and S. Y. Shin, \newblock ``FBI: A Federated Learning-Based Blockchain-Embedded Data Accumulation Scheme Using Drones for Internet of Things," \newblock {\em IEEE Wireless Communications Letters}, vol. 11, no. 5, pp. 972-976, May 2022. \bibitem{Islam2020} A. Islam, S.Y. Shin, \newblock ``A Blockchain-based Secure Healthcare Scheme with the Assistance of Unmanned Aerial Vehicle in Internet of Things,'' \newblock {\em Computers \& Electrical Engineering}, vol. 84, 2020. \bibitem{Islam2021} A. Islam, T. Rahim, M. Masuduzzaman and S. Y. Shin, \newblock ``A Blockchain-Based Artificial Intelligence-Empowered Contagious Pandemic Situation Supervision Scheme Using Internet of Drone Things," \newblock{ \em IEEE Wireless Communications}, vol. 28, no. 4, pp. 166-173, August 2021. \bibitem{Naren:2021} Naren, A. Tahiliani, V. Hassija, V. Chamola, S. S. Kanhere and M. Guizani, \newblock ``Privacy-Preserving and Incentivized Contact Tracing for COVID-19 Using Blockchain,” \newblock {\em IEEE Internet of Things Magazine}, vol. 4, no. 3, pp. 72-79, September 2021. \bibitem{Choo2020} K. R. Choo, Z. Yan, W. Meng, \newblock ``Editorial: Blockchain in Industrial IoT Applications: Security and Privacy Advances, Challenges, and Opportunities," \newblock{ \em IEEE Trans. Ind. Informat.}, vol. 16, no. 6, pp. 4119-4121, 2020. \bibitem{Javaid2020} U. Javaid and B. Sikdar, \newblock ``A Checkpoint Enabled Scalable Blockchain Architecture for Industrial Internet of Things," \newblock{ \em IEEE Trans. Ind. Informat.}, Oct. 2020. \bibitem{Nguyen:2020} D. Nguyen, M. Ding, P. N. Pathirana, A. Seneviratne, \newblock ``Blockchain and ai-based solutions to combat coronavirus (covid19)-like epidemics: A survey,'' Preprints 2020, 2020040325. \bibitem{Zhang2019} L. Zhang, T. Zhang, Q. Wu, Y. Mu and F. Rezaeibagha, \newblock ``Secure Decentralized Attribute-Based Sharing of Personal Health Records with Blockchain," \newblock{ \em IEEE Internet of Things Journal}, 2021. \bibitem{Dai2019} H. -N. Dai, Z. Zheng and Y. Zhang, \newblock ``Blockchain for Internet of Things: A Survey," \newblock {\em IEEE Internet of Things Journal}, vol. 6, no. 5, pp. 8076-8094, Oct. 2019. \bibitem{Wang:2021} P. Wang, C. Lin, M. S. Obaidat, Z. Yu, Z. Wei and Q. Zhang, \newblock ``Contact Tracing Incentive for COVID-19 and Other Pandemic Diseases From a Crowdsourcing Perspective,'' \newblock{ \em IEEE Internet of Things Journal}, vol. 8, no. 21, pp. 15863-15874, 1 Nov.1, 2021. \bibitem{DWang:2022} D. Wang, X. Chen, L. Zhang, Y. Fang and C. Huang, \newblock ``A Blockchain based Human-to-Infrastructure Contact Tracing Approach for COVID-19,'' \newblock{ \em IEEE Internet of Things Journal}, vol. 9, no. 14, pp. 12836-12847, 15 July15, 2022. %[10] \bibitem{Garofalo:2021} G. Garofalo, T. Van hamme, D. Preuveneers, W. Joosen, A. Abidin and M. A. Mustafa, \newblock ``PIVOT: PrIVate and effective cOntact Tracing,'' \newblock{ \em IEEE Internet of Things Journal}, 2021. %[11] \bibitem{Azad:2021} M. A. Azad, \textit{et al.}, \newblock ``A First Look at Privacy Analysis of COVID-19 Contact-Tracing Mobile Applications,'' \newblock{ \em IEEE Internet of Things Journal}, vol. 8, no. 21, pp. 15796-15806, 1 Nov.1, 2021. \bibitem{Song:2021} J. Song, T. Gu, X. Feng, Y. Ge, and P. Mohapatra, \newblock ``Blockchain Meets COVID-19: A Framework for Contact Information Sharing and Risk Notification System,” \newblock {\em IEEE 18th International Conference on Mobile Ad Hoc and Smart Systems}, 2021, pp. 269-277. \bibitem{Ferrag:2021} M. A. Ferrag and L. Shu, \newblock ``The Performance Evaluation of Blockchain-Based Security and Privacy Systems for the Internet of Things: A Tutorial," \newblock{ \em IEEE Int. of Things J.}, vol. 8, no. 24, pp. 17236-17260, 2021. \bibitem{Martinez:2020} M. Martinez, A. Hekmati, B. Krishnamachari and S. Yun, \newblock ``Mobile Encounter-based Social Sybil Control," \newblock{ \em Int. Con. Software Defined Systems (SDS)}, 2020, pp. 190-195. \bibitem{Xu2020} H. Xu, \textit{et al.}, \newblock ``Beeptrace: Blockchain-Enabled Privacy-Preserving Contact Tracing for Covid-19 Pandemic and Beyond," \newblock{ \em IEEE Internet Things J.}, pp. 1-1, Sep. 2020. \bibitem{Hasan:2021} H. R. Hasan, K. Salah, R. Jayaraman, I. Yaqoob, M. Omar and S. Ellahham, \newblock ``COVID-19 Contact Tracing Using Blockchain,” \newblock {\em IEEE Access}, vol. 9, pp. 62956-62971, 2021. \bibitem{Micali2020} S. Micali, \newblock ``Algorand’s approach to Covid-19 tracing," Tech. Rep., 2020. \bibitem{Lv2022} W. Lv, S. Wu, C. Jiang, Y. Cui, X. Qiu, and Y. Zhang, \newblock ``Towards Large-Scale and Privacy-Preserving Contact Tracing in COVID-19 Pandemic: A Blockchain Perspective," \newblock {\em IEEE Transactions on Network Science and Engineering}, vol. 9, no. 1, pp. 282-298, 2022. \bibitem{Avitabile2020} G. Avitabile, V. Botta, V. Iovino, and I. Visconti, \newblock ``Towards defeating mass surveillance and SARS-CoV-2: The pronto-C2 fully decentralized automatic contact tracing system," \newblock IACR Cryptol. ePrint Arch., vol. 2020, p. 493, May 2020. \bibitem{DIMY:2021} N. Ahmed, R. A. Michelin, W. Xue, G. Dharma Putra, S. Ruj, S. S. Kanhere, and S. Jha, \newblock ``DIMY: Enabling privacy-preserving contact tracing,” 2021, arXiv:2103.05873. [Online]. Available: http:// arxiv.org/abs/2103.05873. \bibitem{Peng2021} K. Peng, M. Li, H. Huang, C. Wang, S. Wan and K. -K. R. Choo, \newblock ``Security Challenges and Opportunities for Smart Contracts in Internet of Things: A Survey," \newblock{ \em IEEE Internet of Things Journal}, vol. 8, no. 15, pp. 12004-12020, 2021. \bibitem{Esteves2020} P. Esteves-Verissimo, J. Decouchant, M. Völp, A. Esfahani, and R. Graczyk, \newblock ``PriLok: Citizen-protecting distributed epidemic tracing," 2020, arXiv:2005.04519. [Online]. Available: http://arxiv.org/abs/2005.04519. \bibitem{Yanagihara:2022} T. Yanagihara and A. Fujihara, \newblock ``Cross-Referencing Method for Scalable Public Blockchain,” \newblock {\em Internet of Things Journal}, Volume 15, 100419, 2022. \bibitem{Jing2021} G. Jing, H. Bai, J. George, A. Chakrabortty, \newblock Model-free optimal control of linear multi-agent systems via decomposition and hierarchical approximation. \newblock{ \em IEEE Trans. Control Netw. Syst.}, vol. 8, no. 3, pp. 1069-1081, 2021. %MDPI: Please add volume and page. If no page or volume, please add doi. \bibitem{Turchetta2020} M. Turchetta, A. Krause, S. Trimpe, \newblock ``Robust Model-free Reinforcement Learning with Multi-objective Bayesian Optimization," \newblock In Proceedings of the IEEE International Conference on Robotics and Automation (ICRA), Paris, France, 31 May--31 August, 2020. \bibitem{Liu2020} Q. Liu, T. Yu, Y. Bai, C. Jin, \newblock ``A sharp analysis of model-based reinforcement learning with self-play," \newblock {\em arXiv}, 2020, arXiv:2010.01604. \bibitem{Bellman1954} R. Bellman, \newblock ``The Theory of Dynamic Programming," Tech. Rep., \newblock RAND Corp: Santa Monica, CA, USA, 1954. \bibitem{Vertes} E. V\'{e}rtes,and M. Sahani, \newblock ``A Neurally Plausible Model Learns Successor Representations in Partially Observable Environments," \newblock{ \em Advances in Neural Information Processing Systems 32}, pp.13714-13724, 2019. \bibitem{Sam} S. Blakeman, and D. Mareschal, \newblock ``A Complementary Learning Systems Approach to Temporal Difference Learning," \newblock {\em Neural Networks}, vol. 122, 2020, pp. 218-230. \bibitem{Song2021} Y. Song, W. Sun, \newblock ``Pc-mlp: Model-based reinforcement learning with policy cover guided exploration," \newblock In Proceedings of the International Conference on Machine Learning, Virtual, 18--24 July 2021. \bibitem{Geerts2019} J. P.Geerts, K. L. Stachenfeld, N. Burgess, \newblock ``Probabilistic Successor Representations with Kalman Temporal Differences," \newblock{ \em arXiv}, 2019, arXiv:1910.02532. \bibitem{Machado2021} M. C. Machado, A. Barreto, D. Precup, \newblock ``Temporal Abstraction in Reinforcement Learning with the Successor Representation," \newblock{ \em arXiv},2021, arXiv:2110.05740. \bibitem{Moskovitz2021} T. H. Moskovitz, J. Parker-Holder, A. Pacchiano, M.Arbel, M. I. Jordan, \newblock ``Tactical optimism and pessimism for deep reinforcement learning," \newblock In Proceedings of the NeurIPS, Virtual, 6-14 December 2021. \bibitem{Hasselt2016} H. Van Hasselt, A. Guez, D.Silver, ``Deep Reinforcement Learning with Double Q-Learning," \newblock AAAI: Phoenix, AZ, USA, 2016, p. 5. \bibitem{Babu2012} G. S. Babu, S. Suresh, \newblock ``Meta-cognitive neural network for classification problems in a sequential learning framework," \newblock {\em Neurocomputing},2012,81, 86--96. %6 \bibitem{Riedmiller2005} M. Riedmiller, \newblock ``Neural Fitted Q Iteration-first Experiences with a Data Efficient Neural Reinforcement Learning Method," \newblock {\em European Conference on Machine Learning}; Springer: Berlin, Heidelberg, %MDPI: Please add the location of the publisher. 2005, pp. 317--328. \bibitem{Tang} Y. Tang, H. Guo,T. Yuan, X. Gao, X. Hong, Y. Li, J. Qiu, Y. Zuo, and J. Wu, \newblock ``Flow Splitter: A Deep Reinforcement Learning-Based Flow Scheduler for Hybrid Optical-Electrical Data Center Network," \newblock{\em IEEE Access}, vol. 7, pp.129955-129965, 2019. %\bibitem{Hu} %C. Hu, and M. Xu, %\newblock ``Adaptive Exploration Strategy With Multi-Attribute Decision-Making for Reinforcement Learning," %\newblock{\em IEEE Access}, vol. 8, pp. 32353-32364, 2020. \bibitem{Kim} M. Kim, S. Lee, J. Lim, J. Choi, and S.G. Kang, \newblock ``Unexpected Collision Avoidance Driving Strategy Using Deep Reinforcement Learning," \newblock{\em IEEE Access}, vol. 8, pp. 17243-17252, 2020. \bibitem{Xie} J. Xie, Z. Shao, Y. Li, Y. Guan, and J. Tan, \newblock ``Deep reinforcement learning with optimized reward functions for robotic trajectory planning," \newblock{\em IEEE Access}, vol. 7, pp. 105669-105679, 2019. \bibitem{Mnih2013} V. Mnih, K. Kavukcuoglu, D. Silver, A. Graves, I. Antonoglou, D. Wierstra, M.Riedmiller, \newblock ``Playing Atari with Deep Reinforcement Learning," \newblock Technical Report, Deepmind Technologies: London, %MDPI: Please add the location of the publisher. 2013, arXiv:1312.5602[cs.LG]. \bibitem{Lillicrap2015} T. Lillicrap, J. Hunt, A. Pritzel, N. Heess, T. Erez, Y. Tassa, D. Silver, D. Wierstra, \newblock ``Continuous control with deep reinforcement learning," \newblock {\em arXiv}, 2015, arXiv:1509.02971. \bibitem{Tsitsiklis1997} J.N. Tsitsiklis, B. Van Roy, \newblock ``An analysis of temporal-difference learning with function approximation," \newblock{\em IEEE Transactions on Automatic Control}, 42 (5) (May 1997) 674–690. \bibitem{Bertsekas2004} D.P. Bertsekas, V.S. Borkar, A. Nedic, \newblock ``Improved temporal difference methods with linear function approximation, Learning and Approximate Dynamic Programming," \newblock 2004, pp. 231–255. \bibitem{Miller1990} W. T. Miller, F. H. Glanz, and L. G. Kraft, \newblock ``Cmas: An Associative Neural Network Alternative to Backpropagation," \newblock {\em Proceedings of the IEEE}, vol. 78, no. 10, pp. 1561-1567, 1990. \bibitem{Haykin1994} S. Haykin, \newblock ``Neural Networks: A Comprehensive Foundation,'' \newblock {\em Prentice Hall PTR}, 1994. \bibitem{Barreto2008} A. d. M. S. Barreto and C. W. Anderson, \newblock ``Restricted Gradient-descent Algorithm for Value-function Approximation in Reinforcement Learning," \newblock {\em Artificial Intelligence}, vol. 172, no. 4-5, pp. 454-482, 2008. \bibitem{Menache2005} I. Menache, S. Mannor, and N. Shimkin, \newblock ``Basis Function Adaptation in Temporal Difference Reinforcement Learning," \newblock {\em Annals of Operations Research}, vol. 134, no. 1, pp. 215-238, 2005. \bibitem{Choi2006} D. Choi and B. Van Roy, \newblock ``A generalized Kalman filter for Fixed Point Approximation and Efficient Temporal-difference Learning," \newblock {\em Discrete Event Dynamic Systems}, vol. 16, no. 2, pp. 207-239, 2006. \bibitem{Engel2005} Y. Engel, \newblock ``Algorithms and Representations for Reinforcement Learning,'' \newblock {\em Hebrew University of Jerusalem}, 2005. \bibitem{Bradtke1996} S. J. Bradtke and A. G. Barto, \newblock ``Linear Least-squares Algorithms for Temporal Difference Learning," \newblock {\em Machine Learning}, vol. 22, no. 1-3, pp. 33-57, 1996. %\bibitem{Liu2021} %E.Z. Liu, A. Raghunathan, P. Liang, C. Finn, % \newblock `` Decoupling exploration and exploitation for meta-reinforcement learning without sacrifices," % \newblock {\em International Conference on Machine Learning}, 2021, PMLR. pp. 6925–6935. \bibitem{Geist2013} M. Geist and O. Pietquin, \newblock ``Algorithmic Survey of Parametric Value Function Approximation," \newblock {\em IEEE Transactions on Neural Networks and Learning Systems}, vol. 24, no. 6, pp. 845-867, 2013. \bibitem{Geist2010} M. Geist and O. Pietquin, \newblock ``Kalman Temporal Differences," \newblock {\em Journal of Artificial Intelligence Research}, vol. 39, pp. 483-532, 2010. \bibitem{Arash:TNSRE:2015} A. Mohammadi and K. N. Plataniotis, \newblock ``Distributed Widely Linear Multiple-Model Adaptive Estimation," \newblock {\em IEEE Transactions on Signal and Information Processing over Networks}, vol. 1, no. 3, pp. 164-179, 2015. \bibitem{Arash:Sensors2016} C. Yang, A. Mohammadi, Q-W. Chen, \newblock `` Multi-Sensor Fusion with Interaction Multiple Model and Chi-Square Test Tolerant Filter," \newblock {\em Sensors}, vol. 16, no. 11, 1835, 2016. \bibitem{Arash:TSP:2015} A. Mohammadi and K. N. Plataniotis, \newblock ``Improper Complex-Valued Multiple-Model Adaptive Estimation," \newblock {\em IEEE Transactions on Signal Processing}, vol. 63, no. 6, pp. 1528-1542, 2015. \bibitem{Mehra1970} R. Mehra, \newblock ``On the Identification of Variances and Adaptive Kalman Filtering," \newblock {\em IEEE Transactions on Automatic Control}, vol. 15, no. 2, pp. 175-184, 1970. \bibitem{Assa2018} A. Assa and K. N. Plataniotis, \newblock ``Similarity-based Multiple Model Adaptive Estimation," \newblock {\em IEEE Access}, vol. 6, pp. 36 632-36 644, 2018. \bibitem{Kitao2017} T. Kitao, M. Shirai, and T. Miura, ``Model Selection based on Kalman Temporal Differences Learning," \newblock {\em IEEE International Conference on Collaboration and Internet Computing (CIC)}, 2017, pp. 41-47. \bibitem{Ma2018} C. Ma, J. Wen, and Y. Bengio, \newblock ``Universal successor representations for transfer reinforcement learning," \newblock {\em arXiv preprint}, arXiv:1804.03758, 2018. \bibitem{Momennejad2017} I. Momennejad, E.M. Russek, J.H. Cheong, M.M. Botvinick, N.D. Daw, S.J.Gershman, \newblock ``The successor representation in human reinforcement learning," \newblock {\em Nature Human Behaviour}, 1 (9) (2017) 680–692. \bibitem{Russek2017} E.M. Russek, I. Momennejad, M.M. Botvinick, S.J. Gershman, N.D. Daw, \newblock ``Predictive representations can link model-based reinforcement learning to model-free mechanisms," \newblock {\em PLoS Computational Biology}, 13 (9) (2017) e1005768. \bibitem{Sutton2018} R. S. Sutton and A. G. Barto, \newblock ``Reinforcement Learning: An Introduction," \newblock {\em Cambridge}, MA, USA: MIT Press, 2018. \bibitem{Chan2020} S.C. Chan, S. Fishman, J. Canny, et al., \newblock ``Measuring the reliability of reinforcement learning algorithms," \newblock {\em International Conference on Learning Representations}, 2020. \bibitem{Parvin2021} P. Malekzadeh, M. Salimibeni, M. Hou, A. Mohammadi, K. N. Plataniotis, \newblock ``AKF-SR: Adaptive Kalman Filtering-Based Successor Representation," \newblock {\em Neurocomputing}, vol. 467, no. 7, pp. 476-490, January 2022. \bibitem{Spano} S. Spanò, G.C. Cardarilli, L. Di Nunzio, R. Fazzolari, D. Giardino, M. Matta, A. Nannarelli, and M. Re, \newblock ``An Efficient Hardware Implementation of Reinforcement Learning: The Q-Learning," Algorithm," \newblock {\em IEEE Access}, vol. 7, pp. 186340-186351, 2019. \bibitem{Seo} M. Seo, L.F. Vecchietti, S. Lee, and D. Har, \newblock ``Rewards Prediction-Based Credit Assignment for Reinforcement Learning With Sparse Binary Rewards," \newblock {\em IEEE Access}, vol. 7, pp. 118776-118791, 2019. \bibitem{DrMing1} A. Toubman \textit{et al.}, \newblock ``Modeling behavior of Computer Generated Forces with Machine Learning Techniques, the NATO Task Group approach," \newblock {\em IEEE Int. Con. Systems, Man, and Cyb. (SMC)}, Budapest, 2016, pp. 001906-001911. \bibitem{DrMing2} J. J. Roessingh \textit{et al.}, \newblock ``Machine Learning Techniques for Autonomous Agents in Military Simulations - Multum in Parvo," \newblock {\em IEEE Int. Con. Systems, Man, and Cyb. (SMC)}, Banff, AB, 2017, pp. 3445-3450. %\bibitem{Parvin:access} %P. Malekzadeh, M. Salimibeni, A. Mohammadi, A. Assa and K. N. Plataniotis, %\newblock ``MM-KTD: Multiple Model Kalman Temporal Differences for Reinforcement Learning," %\newblock{\em IEEE Access}, vol. 8, pp. 128716-128729, 2020. \bibitem{Hu} H. Hu, S. Song and C. L. P. Chen, \newblock ``Plume Tracing via Model-Free Reinforcement Learning Method," \newblock{ \em IEEE Transactions on Neural Networks and Learning Systems}, vol. 30, no. 8, pp. 2515-2527, Aug. 2019. \bibitem{Venkat} H. K. Venkataraman, and P. J. Seiler, \newblock ``Recovering Robustness in Model-Free Reinforcement Learning," \newblock{\em American Control Conference (ACC)}, Philadelphia, PA, USA, 2019, pp. 4210-4216. \bibitem{Williams:2017} G. Williams, N. Wagener, B. Goldfain, P. Drews, J. M. Rehg, B. Boots, and E. A. Theodorou, \newblock ``Information Theoretic MPC for Model-based Reinforcement Learning," \newblock {\em International Conference on Robotics and Automation (ICRA)}, 2017. \bibitem{Bellman:1954} R. Bellman, \newblock ``The Theory of Dynamic Programming," \newblock {\em RAND Corp Santa Monica CA}, Tech. Rep., 1954. \bibitem{Ducarouge} A. Ducarouge, O. Sigaud, \newblock ``The Successor Representation as a Model of Behavioural Flexibility," \newblock{ \em Journ{\'e}es Francophones sur la Planification, la D{\'e}cision et l'Apprentissage pour la conduite de syst{\`e}mes (JFPDA)}, 2017. \bibitem{Lazaric:2008} A. Lazaric, M. Restelli, and A. Bonarini, \newblock ````Reinforcement Learning in Continuous Action Spaces Through Sequential Monte Carlo Methods," \newblock {\em Advances in Neural Information Processing Systems}, 2008, pp. 833-840. \bibitem{Castro:2008} D. D. Castro, D. Volkinshtein and R. Meir, \newblock ``Temporal Difference Based Actor Critic Learning - Convergence and Neural Implementation," \newblock {\em Neural Information Processing Systems Conference}, 2008. %5 \bibitem{Keogh:2011} E. Keogh and A. Mueen, \newblock``Curse of Dimensionality," \newblock {\em Encyclopedia of Machine Learning}, Springer, 2011, pp. 257-258. \bibitem{Ge:2019} Y. Ge, F. Zhu, X. Ling, and Q. Liu, \newblock ``Safe Q-Learning Method Based on Constrained Markov Decision Processes," \newblock {\em IEEE Access}, vol. 7, pp. 165007-165017, 2019. %7 \bibitem{Mnih:2013} V. Mnih, K. Kavukcuoglu, D. Silver, A. Graves, I. Antonoglou, D. Wierstra, and M. Riedmiller, \newblock ``Playing Atari with Deep Reinforcement Learning," \newblock {\em arXiv:1312.5602}, 2013. %%8 %\bibitem{Lillicrap:} %T. P. Lillicrap, J. J. Hunt, A. Pritzel, N. Heess, T. Erez, Y. Tassa, D. Silver, and D. Wierstra, %\newblock ``Continuous Control with Deep Reinforcement Learning," %\newblock {\em arXiv:1509.02971}, 2015. %34 \bibitem{Sukhbaatar:2017} S. Sukhbaatar, I. Kostrikov, A. Szlam, and R. Fergus, \newblock ``Intrinsic motivation and automatic curricula via asymmetric self-play,`` \newblock {\em arXiv}, preprint arXiv:1703.05407, 2017. %13 \bibitem{Haykin:1994} S. Haykin, \newblock ``Neural Networks: A Comprehensive Foundation,'' \newblock {\em Prentice Hall PTR}, 1994. %%14 %\bibitem{14} %W. T. Miller, F. H. Glanz, and L. G. Kraft, %\newblock ``Cmas: An Associative Neural Network Alternative to Backpropagation," %\newblock {\em Proceedings of the IEEE}, vol. 78, no. 10, pp. 1561-1567, 1990. %15 \bibitem{Kretchmar:1997} R. M. Kretchmar and C. W. Anderson, \newblock ``Comparison of CMACs and Radial Basis Functions for Local Function Approximators in Reinforcement Learning," \newblock {\em International Conference on Neural Networks}, vol. 2. IEEE, 1997, pp. 834-837. %16 \bibitem{Konidaris:2011} G. Konidaris, S. Osentoski, and P. S. Thomas, ``Value Function Approximation in Reinforcement Learning using the Fourier Basis," \newblock {\em AAAI}, vol. 6, 2011, p. 7. %17 \bibitem{Menache:2005} I. Menache, S. Mannor, and N. Shimkin, \newblock ``Basis Function Adaptation in Temporal Difference Reinforcement Learning," \newblock {\em Annals of Operations Research}, vol. 134, no. 1, pp. 215-238, 2005. \bibitem{Doya:2002} K. Doya, K. Samejima, K.-i. Katagiri, and M. Kawato, \newblock ``Multiple Model-based Reinforcement Learning," \newblock {\em Neural Computation}, 14(6), 1347–1369, 2002. %25 \bibitem{Lainiotis:1976} D. G. Lainiotis, \newblock ``Partitioning: A Unifying Framework for Adaptive Systems, i: Estimation," \newblock {\em Proceedings of the IEEE}, vol. 64, no. 8, pp. 1126-1143, 1976. \bibitem{Khaleghi:2013} B.Khaleghi, A. Khamis, F. O. Karray, and S. N. Razavi \newblock ``Multisensor data fusion: A review of the state-of-the-art,'' \newblock {\em Information Fusion}, Volume 14, Issue 1, July 2013. \bibitem{Federico:2013} C. Federico, \newblock ``A review of data fusion techniques,'' \newblock {\em Sci. World J.}, 1–19, 2013. \bibitem{Meng:2020} T. Meng, X. Jing, Z. Yan, and W. Pedrycz, \newblock ``A survey on machine learning for data fusion,'' \newblock {\em Information Fusion}, Volume 57, 2020. \bibitem{Chen:2020} S. Chen, J. Wang, H. Li, Z. Wang, F. Liu and S. Li, \newblock ``Top-Down Human-Cyber-Physical Data Fusion Based on Reinforcement Learning,'' \newblock {\em IEEE Access}, vol. 8, pp. 134233-134245, 2020. \bibitem{Liu:2021} X. Liu, C. Sun, M. Zhou, C. Wu, B. Peng and P. Li, \newblock ``Reinforcement Learning-Based Multislot Double-Threshold Spectrum Sensing With Bayesian Fusion for Industrial Big Spectrum Data,'' \newblock {\em IEEE Transactions on Industrial Informatics}, vol. 17, no. 5, pp. 3391-3400, May 2021. \bibitem{Guo:2022} J. Guo, Q. Liu and E. Chen, \newblock ``A Deep Reinforcement Learning Method For Multimodal Data Fusion in Action Recognition,'' \newblock {\em IEEE Signal Processing Letters}, vol. 29, pp. 120-124, 2022. % 41 \bibitem{Abirami:2015} T. Abirami, E. Taghavi, R. Tharmarasa, T. Kirubarajan, and A.-C. Boury-Brisset, \newblock ``Fusing social network data with hard data,'' \newblock {\em Proc. 18th Int. Conf. Inf. Fusion (Fusion)}, 2015, pp. 652–658. % 42 \bibitem{Xiao:2020} F. Xiao, \newblock ``A new divergence measure for belief functions in D–S evidence theory for multisensor data fusion,'' \newblock {\em Inf. Sci., } vol. 514, pp. 462–483, Apr. 2020. \bibitem{Zhu:2022} C. Zhu, F. Xiao, Z. Cao, \newblock ``A generalized Rényi divergence for multi-source information fusion with its application in EEG data analysis,'' \newblock {\em Inf. Sci., } vol. 605, pp. 225-243, 2022. % 43 \bibitem{GZhao:2020} G. Zhao, A. Chen, G. Lu, and W. Liu, \newblock ``Data fusion algorithm based on fuzzy sets and D-S theory of evidence,'' \newblock {\em Tsinghua Sci. Technol.,} vol. 25, no. 1, pp. 12–19, Feb. 2020. \bibitem{Surathong:2021} S. Surathong, C. Maisen and P. Piyawongwisal, \newblock ``Modified Fuzzy Dempster-Shafer Theory for Decision Fusion,'' \newblock {\em 13th Int. Conf. on Information Tech. and Elec. Eng. (ICITEE),} 2021, pp. 244-248. \bibitem{Li:2022} J. Li, and Q. Wang, \newblock ``Multi-modal bioelectrical signal fusion analysis based on different acquisition devices and scene settings: Overview, challenges, and novel orientation,'' \newblock {\em Information Fusion,} Volume 79, 2022. \bibitem{Wang:2019} P. Wang, L. T. Yang, J. Li, J. Chen, and S. Hu, \newblock ``Data fusion in cyber-physical-social systems: State-of-the-art and perspectives,'' \newblock {\em Information Fusion,} vol. 51, Nov. 2019. \bibitem{Himeur:2022} Y. Himeur, B. Rimal, A. Tiwary, and A. Amira, \newblock ``Using artificial intelligence and data fusion for environmental monitoring: A review and future perspectives,'' \newblock {\em Information Fusion}, Volume 86–87, 2022. \bibitem{Saha:2020} P. Saha and S. Mukhopadhyay, \newblock ``Multispectral Information Fusion With Reinforcement Learning for Object Tracking in IoT Edge Devices,'' \newblock {\em IEEE Sensors Journal}, vol. 20, no. 8, pp. 4333-4344, April, 2020. \bibitem{Han:2022} Y. Han et al., \newblock ``Deep Reinforcement Learning for Robot Collision Avoidance With Self-State-Attention and Sensor Fusion,'' \newblock {\em IEEE Robotics and Automation Letters,} vol. 7, no. 3, pp. 6886-6893, July 2022. \bibitem{Zhou:2020} T. Zhou, M. Chen and J. Zou, \newblock ``Reinforcement learning based data fusion method for multi-sensors,'' \newblock {\em IEEE/CAA Journal of Automatica Sinica}, vol. 7, no. 6, pp. 1489-1497, November 2020. \bibitem{Liu:2022} P. Liu, F. Bao, X. Yao, C. Zhang, et al., \newblock ``Multi-type data fusion framework based on deep reinforcement learning for algorithmic trading,'' \newblock {\em Applied Intelligence,} 2022. \bibitem{Yu:2022} J. Yu, P. Wang, T. Koike-Akino and P. V. Orlik, \newblock ``Multi-Modal Recurrent Fusion for Indoor Localization,'' \newblock {\em IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)}, 2022. \bibitem{Sou:2022} S. -I. Sou, F. -J. Wu and W. -C. Wu, \newblock ``JoLo: Multi-device Joint Localization based on Wireless Data Fusion,'' \newblock {\em IEEE Transactions on Mobile Computing}, 2022. \bibitem{Dinh:2021} T. -M. T. Dinh, N. -S. Duong and Q. -T. Nguyen, \newblock ``Developing a Novel Real-Time Indoor Positioning System Based on BLE Beacons and Smartphone Sensors,'' \newblock {\em IEEE Sensors Journal}, vol. 21, no. 20, pp. 23055-23068, 15 Oct.15, 2021. % # ##### End of Chapter 2 ##################################################################################### \bibitem{BLE51} M. Woolley, \newblock ``Bluetooth Direction Finding: A Technical Overview,'' \newblock version 1.0, Revision Date: 20 March 2019. \bibitem{Arash:2015-1} X. Zhong, A. Mohammadi, A.B. Premkumar, and A. Asif, \newblock ``A Distributed Particle Filtering Approach for Multiple Acoustic Source Tracking using an Acoustic Vector Sensor Network,'' \newblock {\em Signal Processing}, vol. 108, pp. 589-603, March 2015. \bibitem{Fang:2011} J. Fang, H. Sun, J. Cao, X. Zhang, Y. Tao, \newblock ``A novel calibration method of magnetic compass based on ellipsoid fitting,'' \newblock {\em IEEE Trans. on Instrument. Meas.}, 60, 2053–2061, 2011. % # ##### End of Chapter 3 ##################################################################################### \bibitem{Hutter2008} M. Hutter and S. Legg, \newblock ``Temporal Difference Updating without a Learning Rate," \newblock {\em Advances in Neural Information Processing Systems}, 2008, pp. 705-712. \bibitem{Sutton1996} R. S. Sutton, \newblock ``Generalization in Reinforcement Learning: Successful Examples using Sparse Coarse Coding," \newblock {\em Advances in Neural Information Processing Systems}, 1996, pp. 1038-1044. \bibitem{Xia2019} W. Xia, C. Di, H. Guo, and S. Li, \newblock ``Reinforcement Learning Based Stochastic Shortest Path Finding in Wireless Sensor Networks," \newblock {\em IEEE Access}, vol. 7, pp.157807-157817, 2019. \bibitem{Watkins1992} C. J. Watkins and P. Dayan, \newblock ``Q-learning," \newblock {\em Machine Learning}, vol. 8, no. 3-4, pp. 279-292, 1992. \bibitem{Li2019} J. Li, T. Chai, F. L. Lewis, Z. Ding and Y. Jiang, \newblock ``Off-Policy Interleaved $Q$ -Learning: Optimal Control for Affine Nonlinear Discrete-Time Systems," \newblock {\em IEEE Transactions on Neural Networks and Learning Systems,}, vol. 30, no. 5, pp. 1308-1320, May 2019. \bibitem{Lowe2017} R. Lowe, Y. Wu, A. Tamar, J. Harb, P. Abbeel, and I. Mordatch, \newblock ``Multi-agent actor-critic for mixed cooperative-competitive environments," \newblock {\em Annual Conference on Neural Information Processing Systems (NIPS)}, 2017. \bibitem{Singh2019} A. Singh, T. Jain, and S. Sukhbaatar, \newblock ``Learning when to communicate at scale in multiagent cooperative and competitive tasks,`` \newblock {\em In ICLR}, 2019. \bibitem{AK2} A. Mohammadi and K. N. Plataniotis, \newblock ``Event-Based Estimation With Information-Based Triggering and Adaptive Update," \newblock {\em IEEE Transactions on Signal Processing}, vol. 65, no. 18, pp. 4924-4939, 15 Sept. 2017. \bibitem{Zhang:2021} K. Zhang, Z. Yang, and T. Bacsar, \newblock ``Multi-Agent Reinforcement Learning: A Selective Overview of Theories and Algorithms," \newblock {\em, https://arxiv.org/abs/1911.10635}, springer, 2021. \bibitem{Hamadanian:2022} P. Hamadanian, M. Schwarzkopf, S. Sen and M. Alizadeh, \newblock ``reinforcement learning in time-varying systems: an empirical study,'' \newblock {\em arXiv:2201.05560v1}, 2201.05560v1, 2022. \bibitem{Mordatch2018} I. Mordatch, P. Abbeel, \newblock ``Emergence of grounded compositional language in multi-agent populations.`` \newblock {\em Proc. AAAI Conference of Artificial Intelligence}, 2018. \bibitem{Henderson:2017} Henderson, P.; Islam, R.; Bachman, P.; Pineau, J.; Precup, D.; Meger, D. \newblock Deep Reinforcement Learning that Matters. \emph{arXiv} \newblock \textbf{2017}, arXiv:1709.06560. \bibitem{Chan:2022} S.C. Chan, S. Fishman, J. Canny, et al., \newblock ``Measuring the Reliability of Reinforcement Learning Algorithms," \newblock {\em International Conference on Learning Representations}, Addis Ababa, Ethiopia, 26--30 April, 2020. % ############################################## End of Chapter 4########################################################### \bibitem{HajiAkhondiICASSP2021} Z. HajiAkhondi-Meybodi, M. S. Beni, A. Mohammadi and K. N. Plataniotis, \newblock``Bluetooth Low Energy and CNN-Based Angle of Arrival Localization in Presence of Rayleigh Fading," \newblock {\em IEEE Int. Conf. on Acoustics, Speech and Signal Processing (ICASSP)}, 2021, pp. 7913-7917. \bibitem{Hussain:2018} S. R. Hussain, S. Mehnaz, S. Nirjon, and E. Bertino, \newblock ``Secure seamless bluetooth low energy connection migration for unmodified iot devices,” \newblock {\em IEEE Trans. Mob. Com.}, vol. 17, no. 4, pp. 927–944, 2018. \bibitem{Wood:2014} G. Wood, \newblock ``Ethereum: A secure decentralised generalised transaction ledger,” Ethereum Project Yellow Paper, 2014. \bibitem{Ferrag:2019} M. A. Ferrag, M. Derdour, M. Mukherjee, A. Derhab, L. Maglaras and H. Janicke, \newblock ``Blockchain Technologies for the Internet of Things: Research Issues and Challenges," \newblock{ \em IEEE Internet of Things Journal}, vol. 6, no. 2, pp. 2188-2204, 2019. \bibitem{Ganardi:2018} M. Ganardi, D. Hucke, and M. Lohrey, \newblock``Randomized sliding window algorithms for regular languages," \newblock {\em 45th International Colloquium on Automata, Languages, and Programming, ICALP}, 2018, Czech Republic, pages 127:1–127:13. \bibitem{MicrosoftStride2021} Microsoft, \newblock ``The Stride Threat Model. [Online]. Available: https://docs.microsoft.com/en-us/previous-versions/commerce-server/ee823878(v=cs.20), 2021. \bibitem{Huang:2018} X. Huang, C. Xu, P. Wang, and H. Liu, \newblock ``LNSC: A security model for electric vehicle and charging pile management based on blockchain ecosystem," \newblock{ \em IEEE Access}, vol. 6, pp. 13565–13574, 2018. %[6] \bibitem{Wang:2018} J. Wang, \textit{et al.}, \newblock ``A blockchain based privacy-preserving incentive mechanism in crowdsensing applications," \newblock{ \em IEEE Access}, vol. 6, pp. 17545–17556, 2018. %[7] \bibitem{Lin:2018} C. Lin, D. He, X. Huang, K.-K. R. Choo, and A. V. Vasilakos, \newblock ``BSeIn: A blockchain-based secure mutual authentication with fine-grained access control system for industry 4.0," \newblock{ \em J. Netw. Comput. Appl.}, vol. 116, pp. 42–52, Aug. 2018. \bibitem{Li:2018} L. Li, \textit{et al.}, \newblock ``CreditCoin: A Privacy-Preserving Blockchain-Based Incentive Announcement Network for Communications of Smart Vehicles," \newblock{ \em IEEE Transactions on Intelligent Transportation Systems,}, vol. 19, no. 7, pp. 2204-2220, July 2018. %[9] \bibitem{Malik:2019} S. Malik, V. Dedeoglu, S. S. Kanhere and R. Jurdak, \newblock ``TrustChain: Trust Management in Blockchain and IoT Supported Supply Chains," \newblock{ \em IEEE International Conference on Blockchain}, 2019, pp. 184-193. \bibitem{Ferrari2018} P. Ferrari, A. Flammini, E. Sisinni, S. Rinaldi, D. Brandão and M. S. Rocha, \newblock ``Delay Estimation of Industrial IoT Applications Based on Messaging Protocols," \newblock {\em IEEE Internet of Things Journal}, vol. 67, no. 9, pp. 2188-2199, Sept. 2018. \bibitem{Pass:2017} R. Pass, C. Tech, and L. Seeman, \newblock ``Analysis of the Blockchain Protocol in Asynchronous Networks," \newblock {\em Annual International Conference on the Theory and Applications of Cryptographic Techniques}, Paris, France, May 2017, pp. 643-673. \bibitem{Garay:2015} J. Garay, A. Kiayias, N. Leonardos, \newblock ``The bitcoin backbone protocol: analysis and applications," \newblock {\em Oswald, E., Fischlin, M. (eds.) EUROCRYPT 2015. LNCS}, vol. 9057, pp. 281–310. Springer, Heidelberg 2015. \bibitem{Miyachi:2021} K. Miyachi and T. K. Mackey, \newblock ``hOCBS: A privacy-preserving blockchain framework for healthcare data leveraging an on-chain and off-chain system design Author links open overlay panel,” \newblock {\em Information Processing \& Management Journal}, vol. 58, no. 3, 2021, Art. no. 102535. \bibitem{Zhou2018} Q. Zhou, H. Huang, Z. Zheng and J. Bian, \newblock ``Solutions to Scalability of Blockchain: A Survey,” \newblock {\em IEEE Access}, vol. 8, pp. 16440-16455, 2020. \bibitem{SegWit2015} E. Lombrozo, J. Lau, and P. Wuille, \newblock ``Segregated witness (consensuslayer),” \newblock {\em Bitcoin Core Develop. Team}, Tech. Rep., 2015. \bibitem{lightningnetwork2016} J. Poon and D. Thaddeus, \newblock ``The bitcoin lightning network: Scalable off-chain instant payments,” \newblock 2016. \bibitem{Norvill2018} R. Norvill, B. B. Fiz Pontiveros, R. State and A. Cullen, \newblock ``IPFS for Reduction of Chain Size in Ethereum," \newblock{ \em IEEE Int. Conf. on Internet of Things (iThings)}, 2018, pp. 1121-1128. \bibitem{Delgado2019} S. Delgado-Segura, C. Perez-Sola, G. Navarro-Arribas, and J. Herrera-Joancomarti, \newblock ``Analysis of the Bitcoin UTXO Set," \newblock{ \em Financial Cryptography and Data Security}, Springer Berlin Heidelberg, 2019, pp. 78–91. \bibitem{Stark2018} J. Stark, \newblock ``Making sense of ethereum’s layer 2 scaling solutions: state channels,Plasma, and truebit. Medium," \newblock February 2018, Available at: https://medium.com/l4-media/making-sense-of-ethereums-layer-2-scaling-solutions-state-channels-plasma-and-truebit-22cb40dcc2f4. \bibitem{P6} H. Obeidat, W. Shuaieb, O. Obeidat, and R. Abd-Alhameed, \newblock``A Review of Indoor Localization Techniques and Wireless Technologies," \newblock {\em Wireless Personal Communications}, vol. 119, no. 1 pp. 289-327, 2021. \bibitem{Yousefi2015} S. Yousefi, X. Chang, and B. Champagne, \newblock ``Mobile Localization in Non-Line-of-Sight Using Constrained Square-Root Unscented Kalman Filter," \newblock{ \em IEEE Trans. Veh. Technol.}, vol. 64, no. 5, pp. 2071-2083, May 2015. \bibitem{Stack_Exchange} Available online: https://www.increasebroadbandspeed.co.uk/what-is-a-good-signal-level-or-signal-to-noise-ratio-snr-for-wi-fi(acc. on 21-05-25). \bibitem{Vujicic:2018} D. Vujicic, D. Jagodic, S. Randic, \newblock ``Blockchain technology, bitcoin, and Ethereum: A brief overview,” \newblock {\em Int. Symposium Inf.-Jah.}, 2018, pp. 1-6.