Concept
Automated planning and scheduling
Related lectures (16)
Deliberative Agents: Planning and Strategies
Covers planning with adversaries, heuristic search algorithms, and strategies for games with chance, emphasizing the significance of deliberative agents.
Automated Planning: Modeling and Constraints
Explores automated planning, constraints, and applications in diverse domains, emphasizing the challenges and efficiency of solving planning problems.
Reactive Agents: Decision Processes
Explores reactive agents and decision processes, covering topics such as Markov Decision Processes and real-time agents.
Factored Representations: Planning Efficiency
Explores factored representations for planning, focusing on reducing complexity and improving efficiency through separate feature modeling.
Model-based versus Model-free Reinforcement Learning
Compares model-based and model-free reinforcement learning, highlighting the advantages of the former in adapting to reward changes and planning future actions.
Multiagent Systems: Planning and Coordination
Explores the use of multi-agent systems for planning, coordination, and task assignment among heterogeneous agents.
Infinite-Horizon Problems: Formulation & Complexity
Covers infinite-horizon problems in Applied Probability and Stochastic Processes.
Intelligent Agents: Making Decisions and Planning
Covers intelligent agents, decision-making, planning, machine learning, and game theory.
Model-Based Deep RL: Planning and VAST
Covers model-based reinforcement learning, planning, variational state tabulation, and efficient Q- and V-values updating.
Monte Carlo Tree Search and Alpha Zero
Explores Monte Carlo Tree Search and Alpha Zero in deep reinforcement learning.