Department: PhD in Computer Science
Module Description: In-depth introduction to Artificial Intelligence focusing on techniques that allow intelligent systems to reason effectively with uncertain information and cope limited computational resources. Topics include: problem-solving using search, heuristic search techniques, constraint satisfaction, local search, abstraction and hierarchical search, resource-bounded search techniques, principles of knowledge representation and reasoning, logical inference, reasoning under uncertainty, belief networks, decision theoretic reasoning, planning under uncertainty using Markov decision processes, multi-agent planning, and computational models of bounded rationality.
Papers cited in the syllabus.
Selected AI research papers from BUiD (the list to be updated on regular basis):
