91 citations · 92 across the 8 of their papers we have counts for
11 papers
How Inefficient Is Natural Gradient Descent? From Exact Optimality to Θ( \sqrt{ \log d } ) Divergence
Guni Sharon, Alan Kuhnle
Natural gradient descent (NGD) underlies common methods in ML. For dually flat families, idealized NGD on the forward Kullback--Leibler objective follows the mixture geodesic which…
Stochastic Reset Pathfinding: Path-Level Regret for Cascading Bandits over Graph Paths
Guni Sharon, Wei Zhang
We introduce Stochastic Reset Pathfinding (SRP), an episodic learning problem on a known directed graph with unknown stationary edge success probabilities. In each episode, the age…
Tree of Thoughts as a Classical Heuristic Search Problem: Formal Foundations and Design Patterns
Guni Sharon
Large Language Models (LLMs) have demonstrated remarkable reasoning capabilities, yet their standard generation process -- auto-regressive token prediction -- is inherently myopic…
Policy-Guided Search on Tree-of-Thoughts for Efficient Problem Solving with Bounded Language Model Queries
Sumedh Pendurkar, Guni Sharon
Recent studies explored integrating state-space search algorithms with Language Models (LM) to perform look-ahead on the token generation process, the ''Tree-of-Thoughts'' (ToT), g…
Task Phasing: Automated Curriculum Learning from Demonstrations
Vaibhav Bajaj, Guni Sharon, Peter Stone
Applying reinforcement learning (RL) to sparse reward domains is notoriously challenging due to insufficient guiding signals. Common RL techniques for addressing such domains inclu…
A Joint Imitation-Reinforcement Learning Framework for Reduced Baseline Regret
Sheelabhadra Dey, Sumedh Pendurkar, Guni Sharon +1
In various control task domains, existing controllers provide a baseline level of performance that -- though possibly suboptimal -- should be maintained. Reinforcement learning (RL…
The (Un)Scalability of Heuristic Approximators for NP-Hard Search Problems
Sumedh Pendurkar, Taoan Huang, Sven Koenig +1
The A* algorithm is commonly used to solve NP-hard combinatorial optimization problems. When provided with a completely informed heuristic function, A* solves many NP-hard minimum-…
Technical Report: Hybrid Autonomous Intersection Management
Aaron Parks-Young, Guni Sharon
This document provides technical details regarding the Hybrid-AIM simulator that was used in Sharon and Stone (2017) and Parks-Young and Sharon (2022).
Learning an Interpretable Traffic Signal Control Policy
James Ault, Josiah P. Hanna, Guni Sharon
Signalized intersections are managed by controllers that assign right of way (green, yellow, and red lights) to non-conflicting directions. Optimizing the actuation policy of such…
Traffic Optimization For a Mixture of Self-interested and Compliant Agents
Guni Sharon, Michael Albert, Tarun Rambha +2
This paper focuses on two commonly used path assignment policies for agents traversing a congested network: self-interested routing, and system-optimum routing. In the self-interes…
Overview: Generalizations of Multi-Agent Path Finding to Real-World Scenarios
Hang Ma, Sven Koenig, Nora Ayanian +7
Multi-agent path finding (MAPF) is well-studied in artificial intelligence, robotics, theoretical computer science and operations research. We discuss issues that arise when genera…