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Model for coordination and decision-making among multiple agents
The decentralized partially observable Markov decision process (Dec-POMDP) is a model for coordination and decision-making among multiple agents. It is
Decentralized partially observable Markov decision process
Decentralized_partially_observable_Markov_decision_process
Israeli-American computer scientist
notably within the context of Markov decision processes (MDPs), Partially Observable MDPs (POMDPs), and Decentralized POMDPs (Dec-POMDPs). His research
Shlomo_Zilberstein
Concept in computational complexity theory
constraint logic is NEXPTIME-complete too. Solving a decentralized partially observable Markov decision process is NEXPTIME-complete. Game complexity NP EXPTIME
NEXPTIME
Sub-field of reinforcement learning
In the partially observable setting, the core model is the partially observable stochastic game in the general case, and the decentralized POMDP in
Multi-agent reinforcement learning
Multi-agent_reinforcement_learning
List of concepts in artificial intelligence
partially observable Markov decision process (POMDP) A generalization of a Markov decision process (MDP). A POMDP models an agent decision process in
Glossary of artificial intelligence
Glossary_of_artificial_intelligence
American economist (born 1948)
Roberts, John (1990a). "The Efficiency of Equity in Organizational Decision Processes". The American Economic Review. 80 (2): 1–31. doi:10.1016/0022-0531(90)90048-O
Paul_Milgrom
Scientific discipline
organisms also demonstrated swarm behavior. Decentralized systems are where individuals act based on their own decisions without overarching guidance. Studies
Theoretical_ecology
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DECENTRALIZED PARTIALLY-OBSERVABLE-MARKOV-DECISION-PROCESS
DECENTRALIZED PARTIALLY-OBSERVABLE-MARKOV-DECISION-PROCESS
DECENTRALIZED PARTIALLY-OBSERVABLE-MARKOV-DECISION-PROCESS
DECENTRALIZED PARTIALLY-OBSERVABLE-MARKOV-DECISION-PROCESS
DECENTRALIZED PARTIALLY-OBSERVABLE-MARKOV-DECISION-PROCESS
DECENTRALIZED PARTIALLY-OBSERVABLE-MARKOV-DECISION-PROCESS
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