GGP Course Videos
Comprehensive video series on General Game Playing, covering game description, management, playing strategies, and advanced topics like heuristic search and Monte Carlo methods.
Combining Tree-Search, Generative Models, and Nash Bargaining Concepts in Game-Theoretic Reinforcement Learning
Explore game-theoretic reinforcement learning combining tree-search, generative models, and Nash bargaining concepts for multiagent scenarios and negotiation games.
How Slot Machines Are Advancing the State of the Art in Computer Go AI
Explore Monte Carlo Tree Search in computer Go AI, covering its advantages, UCB1 strategy, and recent refinements like AMAF/RAVE, with insights into ongoing research topics.
AFLOW: Automating Agentic Workflows for Large Language Models
Discover how AFLOW framework optimizes LLM workflows through automated code-based representations, specialized Monte Carlo Tree Search, and reusable operators to enhance AI performance while reducing computational costs.
AI Strategy Optimization Using Monte Carlo Tree Search - From Theory to Implementation
Explore Monte Carlo Tree Search algorithms and their application in AI decision-making, from basic principles to practical implementations in healthcare and financial forecasting.
Test Time Compute: Verifiers and Parallel Sampling - Part 2
Explore advanced inference techniques using verifiers, parallel sampling, and prompt optimization to enhance language model performance and accuracy.
AlphaGo - Mastering the Game of Go with Deep Neural Networks and Tree Search - RL Paper Explained
Comprehensive exploration of AlphaGo's groundbreaking AI system, detailing its neural networks, search algorithms, and innovative techniques that led to defeating professional Go players.
CMU Neural Nets for NLP 2017 - Advanced Search Algorithms
Explore advanced search algorithms for NLP, including beam search and A*-type search, with a focus on their applications, benefits, and challenges in neural network-based language processing.
Neural Nets for NLP 2019 - Advanced Search Algorithms
Explore advanced search algorithms for NLP, including beam search, A* search, and search with future costs. Learn techniques to improve efficiency and effectiveness in natural language processing tasks.
From Tic Tac Toe to AlphaGo - Playing Games with AI and Machine Learning
Explore AI's evolution from simple games to complex challenges like Go, delving into algorithms, neural networks, and breakthroughs that led to AlphaGo's triumph over human champions.
Total War - How AI Can Deliver Entertainment
Explore AI techniques in Total War games, focusing on Monte Carlo Tree Search, profiling, and optimization for complex strategy environments with limited resources.
How do Chess Engines Work - Looking at Stockfish and AlphaZero
Explore chess AI evolution: from Deep Blue's algorithms to Stockfish's Minimax, and AlphaZero's revolutionary self-learning approach using Monte Carlo Tree Search and neural networks.
Write Your Own AI Agent with Monte Carlo Tree Search - Building a Tic-Tac-Toe Game
Master Monte Carlo Tree Search algorithm implementation by building a Tic-Tac-Toe AI agent, exploring its applications in modern AI systems like AlphaGo and O1 models.
Modeling Individuals Without Data via Secondary Task Transfer Learning
Discover a novel transfer learning method for modeling individual behavior using limited data from secondary tasks, outperforming standard approaches in financial health and game design.
Improving LLM Accuracy with Monte Carlo Tree Search
Explore Monte Carlo Tree Search to enhance LLM accuracy, focusing on boosting Llama 3 8B performance. Learn implementation, testing, and limitations through code examples and mathematical problem-solving.
Reward-Guided Tree Search for Enhanced LLM Reasoning
Discover how reward-guided tree search enhances LLM reasoning capabilities through policy models, reward evaluation, and Monte Carlo algorithms for complex mathematical problem-solving.
Scattered Forest Search: A New Algorithm for Code Generation with LLMs
Explore the innovative Scattered Forest Search algorithm for optimizing code generation with LLMs, covering implementation techniques, theoretical foundations, and benchmark performance.