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- 25Artificial Intelligence
- 6Machine Learning
- 4Game Theory
- 4Heuristic Search
- 3Computing Science
- 3Natural Language Processing
- 1Asadi Atui, Kavosh
- 1Brammadesam Manavalan, Yathirajan
- 1Davis, Trevor
- 1Erickson, Graham KS
- 1Faghih Dinevari, Amir Hossein
- 1Hauer, Bradley
Extensive-form games are a powerful framework for modeling sequential multi-agent interactions. In extensive-form games with imperfect information, Nash equilibria are generally used as a solution concept, but computing a Nash equilibrium can be intractable in large games. Instead, a variety of...
Game theoretic solution concepts, such as Nash equilibrium strategies that are optimal against worst case opponents, provide guidance in finding desirable autonomous agent behaviour. In particular, we wish to approximate solutions to complex, dynamic tasks, such as negotiation or bidding in...
With the growing population of the elderly and the decline of population growth rate, developed countries are facing problems in taking care of their elderly. One of the issues that is becoming more severe is the issue of companionship for the aged people, particularly those who chose to live...
Given nothing but the generative model of the environment, Monte Carlo Tree Search techniques have recently shown spectacular results on domains previously thought to be intractable. In this thesis we try to develop generic techniques for temporal abstraction inside MCTS that would allow the...
Reinforcement learning algorithms are conventionally divided into two approaches: a model-based approach that builds a model of the environment and then computes a value function from the model, and a model-free approach that directly estimates the value function. The first contribution of this...
Designing competitive Artificial Intelligence (AI) systems for Real-Time Strategy (RTS) games often requires a large amount of expert knowledge (resulting in hard-coded rules for the AI system to follow). However, aspects of an RTS agent can be learned from human replay data. In this thesis, we...
Games have been used as a testbed for artificial intelligence research since the earliest conceptions of computing itself. The twin goals of defeating human professional players at games, and of solving games outright by creating an optimal computer agent, have helped to drive practical ...
The field of biomedicine is reeling from “information overload”. Indeed, biomedical researchers find it almost impossible to stay current with published literature due to the vast amounts of data being generated and published. As a result, they are turning to text mining. Over the past two...
Pinball is fast-paced arcade-style game of which the origins date back hundreds of years. Game playing robots exist for billiards, foosball, and soccer and each have their own unique challenges. The speed that balls move in pinball machines requires that players have quick reactions. We created...
For many years, traditional boardgames such as Chess, Checkers or Go havebeen the standard environments to test new Artificial Intelligence (AI) algorithms for achieving robust game-playing agents capable of defeating the best human players. Presently, the focus has shifted...