Global ETD Search
Search theses and dissertations gathered from participating repositories worldwide. Every result links back to the library that holds it. No account is needed.
Results
Showing 1 to 20 of 49 for “"tree search"”.
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RESOURCE CONSTRAINT COOPERATIVE GAME WITH MONTE CARLO TREE SEARCH
… methodology of game theory and Monte Carlo Tree Search was developed and the hybrid methodology was tested with various case studies through the nurse scheduling problem to show that it was able to form Pareto front dominance solutions, finding feasible solutions that were optimal and finding …
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Monte Carlo Tree Search Applications to Neural Theorem Proving
… explores solutions to these problems, namely search and verification, following Yang’s recent contribution: LeanDojo: Theorem Proving with Retrieval-Augmented Language Models. In their work, Yang et al. introduce LeanDojo, an environment for programmatic interaction with the Lean theorem …
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Nested Monte Carlo Tree Search as Applied to Samurai Sudoku
… the game for interesting properties. The large search space presents a challenge for both generating and solving Sudoku puzzles without relying on techniques that simply permute a valid puzzle. These permutations result in puzzles that are essentially the same since they follow the same solution …
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Solving planning problems with deep reinforcement learning and tree search
Deep reinforcement learning methods are capable of learning complex heuristics starting with no prior knowledge, but struggle in environments where the learning signal is sparse. In contrast, planning methods can discover the optimal path to a goal in the absence of external rewards, but often …
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Distributed Monte Carlo Tree Search With Applications To Chip Design
Monte Carlo Tree Search is a classic method in AI that builds up a search tree asymmetrically using random rollouts on a game tree. The work detailed in this thesis expands upon traditional implementations by allowing the capability of fully distributing each node onto different physical machines …
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Towards Better Turn-Based Strategy Planning Agents: Turn-Based Evolutionary Tree Search
… where conventional algorithms like Monte Carlo Tree Search (MCTS) and Rolling Horizon Evolutionary Algorithms (RHEA) struggle to scale. First, we perform an investigation into state-of-the-art Deep Learning based models for game agents in TUBSTAP. Then, we propose Turn-Based Evolutionary Tree …
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Solving General Game Playing with Incomplete Information Problem using Iterative Tree Search and Language Learning
… been provided to play games in GGP-II. This research is concerned with three main limitations of algorithms in the literature: valuing-information, generating mixed strategy and cooperating in games which require implicit communication. In this thesis, I theoretically and experimentally show …
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An Intent-based Neural Monte Carlo Tree Search Framework for Synthesis of Printed Circuit Boards
… This paper proposes the usage of Monte Carlo Tree Search (MCTS) augmented to improve search in order to self-generate datasets, culminating in a process called LFS (Learning Feedback System). This process allows using past data to accelerate MCTS with deep RL models on new or similar board …
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MONTE CARLO TREE SEARCH AND MINIMAX COMBINATION – APPLICATION OF SOLVING PROBLEMS IN THE GAME OF GO
Monte Carlo Tree Search (MCTS) has been successfully applied to a variety of games. Its best-first algorithm enables implementations without evaluation functions. Combined with Upper Confidence bounds applied to Trees (UCT), MCTS has an advantage over traditional depth-limited minimax search with …
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Assembly sequencing through graph reasoning : graph grammar rules for assembly planning
… sequences which are run in conjunction with a tree search algorithm. An evaluation system then evaluates partial assembly sequences, which are used by the tree- search to find near-optimal assembly sequences.
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A heuristic method for the optimal design of water distribution systems
… first step considers obtaining a near optimal tree layout using a heuristic tree search algorithm. Two different methods are followed for the tree search - one for single source networks and the other for multiple source networks. The second step adds loop forming redundant links to the tree …
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Artificial intelligence in co-operative games with partial observability
… an environment that an agent can observe. The research performed in this thesis examines the challenge of creating Artificial Intelligence for co-operative games that feature Partial Observability. The main contributions are that Monte-Carlo Tree Search outperforms Genetic Algorithm based agents …
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An Ambulatory Monitoring Algorithm to Unify Diverse E-Textile Garments
… utilizes regular expressions along with a tree search during classification. To validate the approach, a user study was conducted using video motion capture to record subjects performing a variety of activities. The subjects were randomly placed into two groups, one used to generate the …
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A problem solving system employing a formal approach to means
… the framework of means/ends analysis and employs tree search during problem solution. A comparison is made with two other systems using means/ends analysis. The conditions under which the system is capable of solving problems are investigated and the efficiency of the system is considered. The …
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Winning at Pokémon Random Battles Using Reinforcement Learning
… demonstrate an agent which employs a Monte Carlo Tree Search informed by a actor-critic network trained using Proximal Policy Optimization with experience collected through self-play. The agent peaked at rank 8 (1693 Elo) on the official Pokémon Showdown gen4randombattles ladder, which is the best …
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OPTIMIZATION UNDER STOCHASTIC ENVIRONMENT
… such as control engineering, operations research, and computer science. It has found wide applications ranging from path planning (civil engineering) and tool-life testing (industrial engineering) to Go-playing artificial intelligence (computer science). However, SO is usually a hard …
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Humanization of computational learning in strategy games
… games: minimax, alpha-beta pruning, Monte Carlo tree search, and neural networks. I then explain why I do not believe that people use any of these techniques to play strategy games. I support this claim by creating a new strategy game, which I call Tarble, that people are able to play at a far …
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An Introduction to Reinforcement Learning
… policy gradient methods, imitation learning, and tree search-based planning methods. Our contribution to the RL literature is an approachable and concise presentation of core RL algorithms that balances practical considerations with theoretical rigour. Each chapter includes extensive bibliographic …
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Algorithms for pipeline transfer scheduling
… one basic approach was chosen for future research. Specifically this thesis results from an investigation of the feasibility of using a tree-search algorithm based upon a similar approach successfully used in paper machine trim scheduling.
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Application of Retrograde Analysis to Fighting Games
… in two-player fighting games. Monte-Carlo Tree-Search approaches currently dominate the competition, but it is unclear if this is the best approach for all fighting games. In this thesis we study the design of two-player fighting games and the consequences of the game design on the types of …
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