Learning data-driven decision-making policies in multi-agent environments for autonomous systems

Decision-Making Policies for Heterogeneous Autonomous Multi-Agent Systems with Safety Constraints

This paper studies a decision-making problem for heterogeneous multi-agent systems with safety density constraints. An individual agent’s decisionmaking problem is modeled by the standard Markov Decision Process (MDP) formulation. However, an important special case occurs when the MDP states may have limited capacities, hence upper bounds on the expected number of agents in each state are impos...

Data Mining for Decision Making in Multi-Agent Systems

The intelligent agent paradigm has generated such a remarkable interest in many application domains over the last two decades. It is growing to be a continuously evolving and expanding area. Agents, Software Agents or Intelligent Agents are intelligent in the sense that they are adaptive, independent, and possess reasoning capability. They can plan and execute tasks in cooperation with other ag...

Multi-Agent Decision Tree Learning from Distributed Autonomous Data Sources

Trust Decision-Making in Multi-Agent Systems

Trust is crucial in dynamic multi-agent systems, where agents may frequently join and leave, and the structure of the society may often change. In these environments, it may be difficult for agents to form stable trust relationships necessary for confident interactions. Societies may break down when trust between agents is too low to motivate interactions. In such settings, agents should make d...

Game Decision Making in Multi Agent Systems

The system multi-agent (SMA) is a compound system of a set agents, situated ina certain environment and interacting to certain relations. The theory of the games is a formalism which aims at studying the interactions between agents knowing that such interactions can extend from the cooperation to the conflict . The game decision making in a system multi-agent require the players to manage a hig...