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Deep reinforcement learning for the computation offloading in MIMO-based Edge Computing.

, , , , and . Ad Hoc Networks, (March 2023)

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Designing and Implementing B2B Applications Using Argumentative Agents., , , , and . SoMeT, volume 182 of Frontiers in Artificial Intelligence and Applications, page 165-189. IOS Press, (2008)Simulating new markets by introducing new accepting policies for the conventional continuous double auction., , , , and . SpringSim, page 89-97. SCS/ACM, (2008)Deep reinforcement learning for the computation offloading in MIMO-based Edge Computing., , , , and . Ad Hoc Networks, (March 2023)Computational logics and verification techniques of multi-agent commitments: survey., , , , and . Knowl. Eng. Rev., 30 (5): 564-606 (2015)Verification and testing of safety-critical airborne systems: A model-based methodology., , , , and . Comput. Sci. Inf. Syst., 17 (1): 271-292 (2020)Model checking temporal knowledge and commitments in multi-agent systems using reduction., , , , and . Simul. Model. Pract. Theory, (2015)Introduction to the Special Section on Trust and AI., , , , and . ACM Trans. Internet Techn., (2019)A Trust and Energy-Aware Double Deep Reinforcement Learning Scheduling Strategy for Federated Learning on IoT Devices., , , and . ICSOC, volume 12571 of Lecture Notes in Computer Science, page 319-333. Springer, (2020)Cloudchain: A Blockchain-Based Coopetition Differential Game Model for Cloud Computing., , , and . ICSOC, volume 11236 of Lecture Notes in Computer Science, page 146-161. Springer, (2018)Explainable AI-based Federated Deep Reinforcement Learning for Trusted Autonomous Driving., , and . IWCMC, page 318-323. IEEE, (2022)