Intelligent Systems

* Foundational issues in intelligent systems

• State-Operator model of Problem spaces
• Brute-force search
  • Breadth-first search
  • Depth-first search
  • Depth-first search with iterative deepening
• Best-first search (generic best-first, Dijkstra’s algorithm, A*, admissibility of A*)
• Two-player games (minimax search, alpha-beta pruning)
• Advanced Search
  • Genetic algorithms
  • Simulated annealing
  • Local search
• The role of heuristics

• History of Intelligent systems
• Philosophical questions
  • The Turing test
  • Searle’s “Chinese Room” thought experiment
  • Ethical issues in AI
• Fundamental definitions
  • Optimal vs. human-like reasoning
  • Optimal vs. human-like behavior
• Modeling the world
• The role of heuristics

• Resolution and theorem proving
• Nonmonotonic inference
• Probabilistic reasoning
• Bayes theorem

• Review of propositional and predicate logic
• Resolution and theorem proving
• Nonmonotonic inference
• Probabilistic reasoning
• Bayes theorem

* Advanced Knowledge Representation and Reasoning

• Structured representation
  • Frames and objects
  • Description logics
  • Inheritance systems
• Nonmonotonic reasoning
  • Nonclassical logics
  • Default reasoning
  • Belief revision
  • Preference logics
  • Integration of knowledge sources
  • Aggregation of conflicting belief
• Reasoning on action and change
  • Situation calculus
  • Event calculus
  • Ramification problems
• Temporal and spatial reasoning
• Uncertainty
  • Probabilistic reasoning
  • Bayesian nets
  • Fuzzy sets and possibility theory
  • Decision theory
• Knowledge representation for diagnosis, qualitative representation

• Genetic algorithms
• Simulated annealing
• Local search

• Definition of agents
• Successful applications and state-of-the-art agent-based systems
• Agent architectures
  • Simple reactive agents
  • Reactive planners
  • Layered architectures
  • Example architectures and applications
• Agent theory
  • Commitments
  • Intentions
  • Decision-theoretic agents
  • Markov decision processes (MDP)
• Software agents, personal assistants, and information access
  • Collaborative agents
  • Information-gathering agents
  • Believable agents (synthetic characters, modeling emotions in agents)
  • Learning agents
• Multi-agent systems
  • Economically inspired multi-agent systems
  • Collaborating agents
  • Agent teams
  • Agent modeling
  • Multi-agent learning
• Introduction to robotic agents
• Mobile agents

• Deterministic and stochastic grammars
• Parsing algorithms
• Corpus-based methods
• Information retrieval
• Language translation
• Speech recognition

• Definition and examples of machine learning
• Supervised learning
• Decision trees
• Neural networks
• Belief networks
• Nearest neighbor algorithm
• Learning theory
• The problem of overfitting
• Unsupervised learning
• Reinforcement learning
• Support Vector Machines

• Definition and examples of planning systems
• Planning as search
• Operator-based planning
• Propositional planning
• Extending planning systems (case-based, learning, and probabilistic systems)
• Static world planning systems
• Planning and execution
• Planning and robotics

• State-of-the-art robot systems
• Planning vs. reactive control
• Uncertainty in control
• Sensing
• World models
• Configuration space
• Planning
• Sensing
• Robot programming
• Navigation and control