Finding Optimal Solutions for Generalized Quantum State Discrimination Problems

Finding Optimal Solutions to Cooperative Pathfinding Problems

In cooperative pathfinding problems, non-interfering paths that bring each agent from its current state to its goal state must be planned for multiple agents. We present the first practical, admissible, and complete algorithm for solving problems of this kind. First, we propose a technique called operator decomposition, which can be used to reduce the branching factors of many search algorithms...

Utilizing Generalized Learning Automata for Finding Optimal Policies in MMDPs

Multi agent Markov decision processes (MMDPs), as the generalization of Markov decision processes to the multi agent case, have long been used for modeling multi agent system and are used as a suitable framework for Multi agent Reinforcement Learning. In this paper, a generalized learning automata based algorithm for finding optimal policies in MMDP is proposed. In the proposed algorithm, MMDP ...

Finding optimal solutions for covering and matching problems

Finding Optimal Solutions for Voting Game Design Problems

In many circumstances where multiple agents need to make a joint decision, voting is used to aggregate the agents’ preferences. Each agent’s vote carries a weight, and if the sum of the weights of the agents in favor of some outcome is larger than or equal to a given quota, then this outcome is decided upon. The distribution of weights leads to a certain distribution of power. Several ‘power in...

Generalized B-spline functions ‎method‎‎ for solving optimal control problems

‎In this paper we introduce a numerical approach that solves optimal control problems (OCPs) ‎using collocation methods‎. ‎This approach is based upon B-spline functions‎. ‎The derivative matrices between any two families of B-spline functions are utilized to‎ ‎reduce the solution of OCPs to the solution of nonlinear optimization problems‎. ‎Numerical experiments confirm our heoretical findings‎.