Understanding and Improving Local Exploration for GBFS
... UHRs. The current work analyzes the reasons for this improvement in detail. The analysis will illustrate that a search method such as GBFS, which uses a global open list, can become stuck in the union of many distinct UHRs from different parts of the search space, which combine to form a large virtu ...
... UHRs. The current work analyzes the reasons for this improvement in detail. The analysis will illustrate that a search method such as GBFS, which uses a global open list, can become stuck in the union of many distinct UHRs from different parts of the search space, which combine to form a large virtu ...
Beyond Adversarial: The Case for Game AI as Storytelling
... On the surface, searching for a move that maximizes the utility of a trajectory appears complicated.A move transitions the agent from one state to another state.How does the agent know what the trajectory will look like?Part of the trajectory is the history of all moves that preceded the current mov ...
... On the surface, searching for a move that maximizes the utility of a trajectory appears complicated.A move transitions the agent from one state to another state.How does the agent know what the trajectory will look like?Part of the trajectory is the history of all moves that preceded the current mov ...
Lifted Backward Search for General Game Playing
... estimation of the true utility value of the state w. Unfortunately, since these rollouts are random, one needs to perform a lot of them before the result becomes accurate. We propose to increase the accuracy by combining MCTS with Lifted-BackwardSearch. The idea is that, before applying MCTS, the pl ...
... estimation of the true utility value of the state w. Unfortunately, since these rollouts are random, one needs to perform a lot of them before the result becomes accurate. We propose to increase the accuracy by combining MCTS with Lifted-BackwardSearch. The idea is that, before applying MCTS, the pl ...
Cooperative Games with Monte Carlo Tree Search
... Abstract— Monte Carlo Tree Search approach with Pareto optimality and pocket algorithm is used to solve and optimize the multi-objective constraint-based staff scheduling problem. The proposed approach has a two-stage selection strategy and the experimental results show that the approach is able to ...
... Abstract— Monte Carlo Tree Search approach with Pareto optimality and pocket algorithm is used to solve and optimize the multi-objective constraint-based staff scheduling problem. The proposed approach has a two-stage selection strategy and the experimental results show that the approach is able to ...
A Competitive Texas Hold’em Poker Player Via Automated Abstraction and
... game theory-based strategies for larger games. Koller and Pfeffer (1997) determined solutions to poker games with up to 140,000 nodes using the sequence form and linear programming. For a medium-sized (3.1 billion nodes) variant of poker called Rhode Island Hold’em, game theory-based solutions have ...
... game theory-based strategies for larger games. Koller and Pfeffer (1997) determined solutions to poker games with up to 140,000 nodes using the sequence form and linear programming. For a medium-sized (3.1 billion nodes) variant of poker called Rhode Island Hold’em, game theory-based solutions have ...
Anytime A* Algorithm – An Extension to A* Algorithm
... approach uses a control manager class which takes care of the time limit and the stopping and restarting of the A* algorithm to find an initial, possibly suboptimal solution, and then continues to search for improved solutions until meeting to a provably optimal solution. It also bounds the sub-opti ...
... approach uses a control manager class which takes care of the time limit and the stopping and restarting of the A* algorithm to find an initial, possibly suboptimal solution, and then continues to search for improved solutions until meeting to a provably optimal solution. It also bounds the sub-opti ...
