Engineering Notes
Thoughts and Ideas on AI by Muthukrishnan
Tag: Algorithms
Anytime Heuristic Search How Agents Find Good Plans Fast and Improve Them Over Time
Anytime heuristic search, including Weighted A* and ARA*, lets agents commit to a suboptimal plan immediately and refine it as time allows, with provable bounds on solution quality at every step.Constraint Satisfaction Problems for Valid Solutions in Complex Agent Planning
Master constraint satisfaction problems (CSP) - a fundamental technique for agent planning, scheduling, and configuration tasks where finding any valid solution is the goal.Multi-Armed Bandits and the Exploration-Exploitation Dilemma in Agent Learning
Master the fundamental problem of sequential decision-making under uncertainty and learn how AI agents balance trying new actions versus exploiting known rewardsContextual Bandits for Balancing Exploration and Exploitation in Real-Time
Master contextual bandits—the algorithm behind personalized recommendations, A/B testing, and adaptive agents. Learn how to balance exploration and exploitation in real-time decision-making.Planning with Backtracking and Replanning for Resilient Adaptive Agents
Learn how backtracking and replanning enable AI agents to recover from failures and adapt to dynamic environmentsMonte Carlo Tree Search from Games to LLMs
## Concept Introduction **Monte Carlo Tree Search (MCTS)** is a heuristic search algorithm for finding optimal decisio...