Reinforcement learning for cooperating and communicating reactive agents in electrical power grids

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

Volumn 2103, Issue , 2001, Pages 137-149

  Riedmiller, Martin ^a   Moore, Andrew ^b   Schneider, Jeff ^b  

^a UNIVERSITY OF KARLSRUHE   (Germany)

^b CARNEGIE MELLON UNIVERSITY   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

ARTIFICIAL INTELLIGENCE; AUTONOMOUS AGENTS; BEHAVIORAL RESEARCH; DYNAMIC PROGRAMMING; ELECTRIC LOAD FLOW; ELECTRIC POWER DISTRIBUTION; ELECTRIC POWER SYSTEM CONTROL; ELECTRIC POWER TRANSMISSION NETWORKS; GLOBAL OPTIMIZATION; INTELLIGENT AGENTS; PROBLEM SOLVING; REINFORCEMENT LEARNING; MULTI AGENT SYSTEMS;

COMMUNICATION MECHANISMS; DISTRIBUTED SYSTEMS; INDIVIDUAL AGENT; INTELLIGENT AGENT SYSTEM; MULTI-AGENT APPROACH; NETWORK CONFIGURATION; REASONING TECHNIQUES; SOCIAL BEHAVIOUR; ELECTRICAL POWER; GLOBAL PROBLEMS; MULTI AGENT SYSTEM (MAS); POWER FLOWS; REACTIVE AGENT;

MULTI AGENT SYSTEMS; PROBLEM SOLVING;

EID: 84864835333     PISSN: 03029743     EISSN: 16113349     Source Type: Book Series    
DOI: 10.1007/3-540-44568-4_9     Document Type: Conference Paper

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