
Explore a novel learning-based strategy for disjunctive static bug-finders, addressing challenges in state-selection heuristics and improving efficiency in real-world program analysis.

Explore algorithmic techniques and data structures for AI problem-solving, applying learned concepts to simple games through hands-on assignments.

Explore algorithmic techniques and data structures for AI problem-solving, applying learned concepts to simple games in this graduate-level introduction to Artificial Intelligence.

Explore computational optimization with Professor Ruth Misener as she shares insights and personal experiences in her inaugural lecture at Imperial College London.

Delve into decision tree construction using the ID3 heuristic algorithm through practical examples and step-by-step implementation for machine learning applications.

Explore probabilistic models for elliptic curve arithmetic, examining theoretical evidence and predictions for higher-dimensional abelian varieties.

Explore search optimizations in AI, including techniques for efficient problem-solving and algorithm enhancement. Learn practical applications through game-related assignments.

Explore AI techniques for video games, including movement, planning, decision-making, and procedural content generation. Implement a bot for a retail game using C++ and SFML.

Explore problem-solving techniques and search algorithms in AI, applying learned concepts to simple games for practical understanding.

Explore Minimax and AlphaBeta Search algorithms for game AI, learning key techniques to optimize decision-making in adversarial environments.