A Concise Introduction to Decentralized POMDPs by Frans A. Oliehoek, Christopher Amato

By Frans A. Oliehoek, Christopher Amato

This e-book introduces multiagent making plans lower than uncertainty as formalized by means of decentralized partly observable Markov choice methods (Dec-POMDPs). The meant viewers is researchers and graduate scholars operating within the fields of synthetic intelligence on the topic of sequential choice making: reinforcement studying, decision-theoretic making plans for unmarried brokers, classical multiagent making plans, decentralized keep watch over, and operations examine.

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A decentralized partially observable Markov decision process is defined as a tuple MDecP = D,S,A,T,O,O,R,h,b0 , where • • • • 1 D = {1, . . ,n} is the set of n agents. S is a (finite) set of states. A is the set of joint actions. T is the transition probability function. Pynadath and Tambe [2002] introduced a model called multiagent team decision problem (MTDP), which is essentially equivalent to the Dec-POMDP. 2 Multiagent Decision Making: Decentralized POMDPs  15         Fig. 3: Schematic representation of a Dec-POMDP.

The states in si ∈ Si are the local states associated with agent i. 4 For example, consider an agent navigation task where the agents are located in positions in a grid and the goal is for all agents to navigate to a particular grid cell. In such a task, an agent’s local state, si , might consist of its location in a grid. Next, we identify some properties that an agent-wise factored Dec-MDP might posses. An agent-wise factored Dec-MDP is said to be locally fully observable if each agent fully observes its own state component.

O is the observation probability function. R is the immediate reward function. h is the horizon of the problem as mentioned above. 2 The Dec-POMDP model extends single-agent POMDP models by considering joint actions and observations. In particular, A = ×i∈D Ai is the set of joint actions. Here, Ai is the set of actions available to agent i, which can be different for each agent. 3 How this joint action influences the environment is described by the transition function T , which specifies Pr(s |s,a).

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