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Found 5 papers, 0 papers with code
Causal Explanations for Sequential Decision Making Under Uncertainty
We introduce a novel framework for causal explanations of stochastic, sequential decision-making systems built on the well-studied structural causal model paradigm for causal reasoning.
Learning Cooperation and Online Planning Through Simulation and Graph Convolutional Network
Against this background, we introduce a simulation based online planning algorithm, that we call SiCLOP, for multi-agent cooperative environments.
On Population-Based Algorithms for Distributed Constraint Optimization Problems
The main characteristic of these algorithms is that they maintain a population of candidate solutions of a given problem and use this population to cover a large area of the search space and to avoid local-optima.
Learning Optimal Temperature Region for Solving Mixed Integer Functional DCOPs
Distributed Constraint Optimization Problems (DCOPs) are an important framework for modeling coordinated decision-making problems in multi-agent systems with a set of discrete variables.
AED: An Anytime Evolutionary DCOP Algorithm
Evolutionary optimization is a generic population-based metaheuristic that can be adapted to solve a wide variety of optimization problems and has proven very effective for combinatorial optimization problems.
