5 papers · 1 filter
Agent-Temporal Credit Assignment for Optimal Policy Preservation in Sparse Multi-Agent Reinforcement Learning
Aditya Kapoor, Sushant Swamy, Kale-ab Tessera +4
In multi-agent environments, agents often struggle to learn optimal policies due to sparse or delayed global rewards, particularly in long-horizon tasks where it is challenging to…
On Linear Convergence of PI Consensus Algorithm under the Restricted Secant Inequality
Kushal Chakrabarti, Mayank Baranwal
This paper considers solving distributed optimization problems in peer-to-peer multi-agent networks. The network is synchronous and connected. By using the proportional-integral (P…
Distributed Optimization via Energy Conservation Laws in Dilated Coordinates
Mayank Baranwal, Kushal Chakrabarti
Continuous-time models can reveal accelerated structures in distributed optimization, but their rates need not survive direct discretization. We introduce a second-order primal--du…
A Methodology Establishing Linear Convergence of Adaptive Gradient Methods under PL Inequality
Kushal Chakrabarti, Mayank Baranwal
Adaptive gradient-descent optimizers are the standard choice for training neural network models. Despite their faster convergence than gradient-descent and remarkable performance i…
ReactAIvate: A Deep Learning Approach to Predicting Reaction Mechanisms and Unmasking Reactivity Hotspots
Ajnabiul Hoque, Manajit Das, Mayank Baranwal +1
A chemical reaction mechanism (CRM) is a sequence of molecular-level events involving bond-breaking/forming processes, generating transient intermediates along the reaction pathway…