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201205s2020 xx o 000 0 eng d |
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|a EBLCP
|b eng
|c EBLCP
|d N$T
|d EBLCP
|d N$T
|d OCLCO
|d OCLCF
|d OCLCO
|d OCLCQ
|d OCLCO
|d OCLCL
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| 020 |
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|a 1119698995
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| 020 |
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|a 9781119698999
|q (electronic bk.)
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| 035 |
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|a (OCoLC)1225551708
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|a Q325.6
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| 082 |
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|a 006.3/1
|2 23
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| 049 |
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|a UAMI
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| 100 |
1 |
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|a Sadhu, Arup Kumar.
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| 245 |
1 |
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|a Multi-Agent Coordination
|h [electronic resource] :
|b A Reinforcement Learning Approach.
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| 260 |
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|a Newark :
|b John Wiley & Sons, Incorporated,
|c 2020.
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| 300 |
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|a 1 online resource (321 p.).
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| 490 |
1 |
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|a Wiley - IEEE Ser.
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| 500 |
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|a Description based upon print version of record.
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0 |
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|a Cover -- Title Page -- Copyright Page -- Contents -- Preface -- Acknowledgments -- Chapter 1 Introduction: Multi-agent Coordination by Reinforcement Learning and Evolutionary Algorithms -- 1.1 Introduction -- 1.2 Single Agent Planning -- 1.2.1 Terminologies Used in Single Agent Planning -- 1.2.2 Single Agent Search-Based Planning Algorithms -- 1.2.2.1 Dijkstra's Algorithm -- 1.2.2.2 A* (A-star) Algorithm -- 1.2.2.3 D* (D-star) Algorithm -- 1.2.2.4 Planning by STRIPS-Like Language -- 1.2.3 Single Agent RL -- 1.2.3.1 Multiarmed Bandit Problem -- 1.2.3.2 DP and Bellman Equation
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| 505 |
8 |
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|a 1.2.3.3 Correlation Between RL and DP -- 1.2.3.4 Single Agent Q-Learning -- 1.2.3.5 Single Agent Planning Using Q-Learning -- 1.3 Multi-agent Planning and Coordination -- 1.3.1 Terminologies Related to Multi-agent Coordination -- 1.3.2 Classification of MAS -- 1.3.3 Game Theory for Multi-agent Coordination -- 1.3.3.1 Nash Equilibrium -- 1.3.3.2 Correlated Equilibrium -- 1.3.3.3 Static Game Examples -- 1.3.4 Correlation Among RL, DP, and GT -- 1.3.5 Classification of MARL -- 1.3.5.1 Cooperative MARL -- 1.3.5.2 Competitive MARL -- 1.3.5.3 Mixed MARL -- 1.3.6 Coordination and Planning by MAQL
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| 505 |
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|a 1.3.7 Performance Analysis of MAQL and MAQL-Based Coordination -- 1.4 Coordination by Optimization Algorithm -- 1.4.1 PSO Algorithm -- 1.4.2 Firefly Algorithm -- 1.4.2.1 Initialization -- 1.4.2.2 Attraction to Brighter Fireflies -- 1.4.2.3 Movement of Fireflies -- 1.4.3 Imperialist Competitive Algorithm -- 1.4.3.1 Initialization -- 1.4.3.2 Selection of Imperialists and Colonies -- 1.4.3.3 Formation of Empires -- 1.4.3.4 Assimilation of Colonies -- 1.4.3.5 Revolution -- 1.4.3.6 Imperialistic Competition -- 1.4.4 Differential Evolution Algorithm -- 1.4.4.1 Initialization -- 1.4.4.2 Mutation
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|a 1.4.4.3 Recombination -- 1.4.4.4 Selection -- 1.4.5 Off-line Optimization -- 1.4.6 Performance Analysis of Optimization Algorithms -- 1.4.6.1 Friedman Test -- 1.4.6.2 Iman-Davenport Test -- 1.5 Summary -- References -- Chapter 2 Improve Convergence Speed of Multi-Agent Q-Learning for Cooperative Task Planning -- 2.1 Introduction -- 2.2 Literature Review -- 2.3 Preliminaries -- 2.3.1 Single Agent Q-learning -- 2.3.2 Multi-agent Q-learning -- 2.4 Proposed MAQL -- 2.4.1 Two Useful Properties -- 2.5 Proposed FCMQL Algorithms and Their Convergence Analysis -- 2.5.1 Proposed FCMQL Algorithms
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|a 2.5.2 Convergence Analysis of the Proposed FCMQL Algorithms -- 2.6 FCMQL-Based Cooperative Multi-agent Planning -- 2.7 Experiments and Results -- 2.8 Conclusions -- 2.9 Summary -- 2.A More Details on Experimental Results -- 2.A.1 Additional Details of Experiment 2.1 -- 2.A.2 Additional Details of Experiment 2.2 -- 2.A.3 Additional Details of Experiment 2.4 -- References -- Chapter 3 Consensus Q-Learning for Multi-agent Cooperative Planning -- 3.1 Introduction -- 3.2 Preliminaries -- 3.2.1 Single Agent Q-Learning -- 3.2.2 Equilibrium-Based Multi-agent Q-Learning -- 3.3 Consensus
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| 590 |
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|a ProQuest Ebook Central
|b Ebook Central Academic Complete
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| 650 |
|
0 |
|a Reinforcement learning.
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| 650 |
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0 |
|a Multiagent systems.
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| 650 |
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6 |
|a Apprentissage par renforcement (Intelligence artificielle)
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| 650 |
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6 |
|a Systèmes multiagents (Intelligence artificielle)
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| 650 |
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7 |
|a Multiagent systems
|2 fast
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| 650 |
|
7 |
|a Reinforcement learning
|2 fast
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| 700 |
1 |
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|a Konar, Amit.
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| 758 |
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|i has work:
|a Multi-Agent Coordination (Text)
|1 https://id.oclc.org/worldcat/entity/E39PCFxfTp9BP6CCMTg6ccVqDC
|4 https://id.oclc.org/worldcat/ontology/hasWork
|
| 776 |
0 |
8 |
|i Print version:
|a Sadhu, Arup Kumar
|t Multi-Agent Coordination : A Reinforcement Learning Approach
|d Newark : John Wiley & Sons, Incorporated,c2020
|z 9781119699033
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| 830 |
|
0 |
|a Wiley - IEEE Ser.
|
| 856 |
4 |
0 |
|u https://ebookcentral.uam.elogim.com/lib/uam-ebooks/detail.action?docID=6413914
|z Texto completo
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| 938 |
|
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|a ProQuest Ebook Central
|b EBLB
|n EBL6413914
|
| 938 |
|
|
|a EBSCOhost
|b EBSC
|n 2692266
|
| 994 |
|
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|a 92
|b IZTAP
|
