V-Learning - Simple, Efficient, Decentralized Algorithm for Multiagent RL
Explore efficient decentralized algorithms for multiagent reinforcement learning, focusing on V-learning's ability to overcome challenges in joint action spaces and achieve Nash equilibria.
Understanding and Extending the Quasipolynomial Time Algorithms for Parity Games
Explore quasipolynomial algorithms for parity games, universal trees, and their extensions to universal graphs. Discover recent advancements in game-solving algorithms and complexity bounds.
Tropical Solutions to Hard Problems in Auction Theory and Neural Networks - Lecture II
Explore tropical mathematics and its applications in neural networks, auction theory, and more, focusing on key ideas of tropical objects as limits and their polyhedral geometry.
Tropical Solutions to Hard Problems in Auction Theory and Neural Networks - Lecture I
Explore tropical mathematics and its applications in neural networks, auction theory, and more. Learn about min-plus algebra, tropical objects, and polyhedral geometry to solve complex problems.
The Miner's Dilemma
Explores the game theory of cryptocurrency mining pools, analyzing strategies and equilibria when pools infiltrate each other, potentially leading to a tragedy of the commons scenario.
The Power of Self-Learning Systems
Explore cutting-edge AI breakthroughs and their implications for scientific discovery with DeepMind's CEO. Learn about self-learning systems, game-changing algorithms, and applications beyond gaming.
Demis Hassabis: Towards General Artificial Intelligence
Explore cutting-edge AI research with DeepMind's CEO, covering breakthroughs like AlphaGo and potential impacts on science and healthcare. Gain insights into AI's future and its implications for understanding human cognition.
The Problem of Governance in Distributed Ledger Technologies - Professor Vili Lehdonvirta, OII
Explore governance challenges in distributed ledger technologies, examining economic organization, cooperation problems, and solutions through the lens of Bitcoin's development and debates.
AI- From Algorithms to Ethics - ACM WomENcourage 2020
Explore AI agents designed for human interaction, combining machine learning, behavioral models, and game theory. Learn about applications in emergency triage and evaluation methodologies.
The Communication Complexity of Truthful vs Non-Truthful Combinatorial Auctions
Explore communication complexity in combinatorial auctions, comparing truthful and non-truthful mechanisms through theoretical analysis and proof techniques.
Multi-Agent Reinforcement Learning - Part II
Explore advanced concepts in multi-agent reinforcement learning, including equilibrium, rewards, and techniques like Q-value and no-regret learning. Gain insights into challenges and applications in AI and game theory.
Multi-Agent Reinforcement Learning - Part I
Explore multi-agent reinforcement learning, covering game theory, interaction protocols, and Nash equilibrium. Gain insights into challenges and formulations in this emerging field.
Independent Learning Dynamics for Stochastic Games - Where Game Theory Meets
Explore independent learning dynamics in stochastic games, bridging game theory and reinforcement learning. Discover convergent algorithms for multi-agent scenarios in dynamic environments.
Machine Learning and Game Theory for Social Impact
Explore machine learning and game theory applications in security, sustainability, and food rescue, featuring real-world deployments and innovative solutions for societal challenges.
Multi-Agent Common Sense - IPAM at UCLA
Explore multi-agent common sense through mathematical frameworks combining Bayesian learning and game theory. Discover insights into human collaboration, joint intentions, and cultural knowledge acquisition.
Flash Loans, Miner Extractable Value and Efficient Settlement - Joint with Alfred Lehar
Explore flash loans, miner extractable value, and efficient settlement in blockchain systems. Gain insights into decentralized finance challenges and potential solutions.
Introduction to Deep Learning with Applications to Stochastic Control and Games
Explore deep learning applications in stochastic control and games, focusing on key concepts and practical implementations for quantitative finance professionals.
Games: From Logic and Automata to Algorithms
Explore the intersection of logic, automata, and algorithms through game theory, focusing on theoretical foundations and computational applications.
Computational Transcendence for Emergent Responsible Autonomy
Explore computational transcendence in autonomous systems, examining its impact on decision-making in supply chains and traffic management for enhanced efficiency and responsibility.
Approximation Schemes for a Unit-Demand Buyer with Independent Items via Symmetries
Explore approximation schemes for unit-demand buyers using symmetries, focusing on independent items and their implications in algorithmic game theory and mechanism design.
Theoretical Foundations of Reinforcement Learning
Explore key concepts and mathematical principles underlying reinforcement learning algorithms, including Markov decision processes, value functions, and policy optimization techniques.