b'Katia Sycara'

research

∙ 06/05/2022

ARC – Actor Residual Critic for Adversarial Imitation Learning

Adversarial Imitation Learning (AIL) is a class of popular state-of-the-...

Ankur Deka, et al. ∙

research

∙ 06/03/2022

The Before, During, and After of Multi-Robot Deadlock

Collision avoidance for multirobot systems is a well-studied problem. Re...

Jaskaran Grover, et al. ∙

research

∙ 04/22/2022

Noncooperative Herding With Control Barrier Functions: Theory and Experiments

In this paper, we consider the problem of protecting a high-value unit f...

Jaskaran Grover, et al. ∙

research

∙ 02/27/2022

Configuration Control for Physical Coupling of Heterogeneous Robot Swarms

In this paper, we present a heterogeneous robot swarm system that can ph...

Sha Yi, et al. ∙

research

∙ 02/06/2022

PuzzleBots: Physical Coupling of Robot Swarms

Robot swarms have been shown to improve the ability of individual robots...

Sha Yi, et al. ∙

research

∙ 01/26/2022

Probe-Based Interventions for Modifying Agent Behavior

Neural nets are powerful function approximators, but the behavior of a g...

Mycal Tucker, et al. ∙

research

∙ 01/19/2022

The Enforcers: Consistent Sparse-Discrete Methods for Constraining Informative Emergent Communication

Communication enables agents to cooperate to achieve their goals. Learni...

Seth Karten, et al. ∙

research

∙ 08/04/2021

Emergent Discrete Communication in Semantic Spaces

Neural agents trained in reinforcement learning settings can learn to co...

Mycal Tucker, et al. ∙

research

∙ 07/31/2021

Learning Embeddings that Capture Spatial Semantics for Indoor Navigation

Incorporating domain-specific priors in search and navigation tasks has ...

Vidhi Jain, et al. ∙

research

∙ 04/07/2021

Deep Interpretable Models of Theory of Mind For Human-Agent Teaming

When developing AI systems that interact with humans, it is essential to...

Ini Oguntola, et al. ∙

research

∙ 03/10/2021

Hiding Leader's Identity in Leader-Follower Navigation through Multi-Agent Reinforcement Learning

Leader-follower navigation is a popular class of multi-robot algorithms ...

Ankur Deka, et al. ∙

research

∙ 03/07/2021

Adaptive Agent Architecture for Real-time Human-Agent Teaming

Teamwork is a set of interrelated reasoning, actions and behaviors of te...

Tianwei Ni, et al. ∙

research

∙ 12/18/2020

Online Connectivity-aware Dynamic Deployment for Heterogeneous Multi-Robot Systems

In this paper, we consider the dynamic multi-robot distribution problem ...

Chendi Lin, et al. ∙

research

∙ 11/15/2020

Predicting Human Strategies in Simulated Search and Rescue Task

In a search and rescue scenario, rescuers may have different knowledge o...

Vidhi Jain, et al. ∙

research

∙ 11/08/2020

Feasible Region-based Identification Using Duality (Extended Version)

We consider the problem of estimating bounds on parameters representing ...

Jaskaran Grover, et al. ∙

research

∙ 09/29/2020

Parameter Identification for Multirobot Systems Using Optimization Based Controllers (Extended Version)

This paper considers the problem of parameter identification for a multi...

Jaskaran Singh Grover, et al. ∙

research

∙ 09/20/2020

Addressing reward bias in Adversarial Imitation Learning with neutral reward functions

Generative Adversarial Imitation Learning suffers from the fundamental p...

Rohit Jena, et al. ∙

research

∙ 08/18/2020

Learning Complex Multi-Agent Policies in Presence of an Adversary

In recent years, there has been some outstanding work on applying deep r...

Siddharth Ghiya, et al. ∙

research

∙ 08/04/2020

Explanation of Reinforcement Learning Model in Dynamic Multi-Agent System

Recently, there has been increasing interest in transparency and interpr...

Xinzhi Wang, et al. ∙

research

∙ 07/06/2020

Natural Emergence of Heterogeneous Strategies in Artificially Intelligent Competitive Teams

Multi agent strategies in mixed cooperative-competitive environments can...

Ankur Deka, et al. ∙

research

∙ 04/10/2020

MA 3 : Model Agnostic Adversarial Augmentation for Few Shot learning

Despite the recent developments in vision-related problems using deep ne...

Rohit Jena, et al. ∙

research

∙ 01/21/2020

Loss-annealed GAIL for sample efficient and stable Imitation Learning

Imitation learning is the problem of learning a policy from an expert po...

Rohit Jena, et al. ∙

research

∙ 12/24/2019

Simultaneous Identification of Tweet Purpose and Position

Tweet classification has attracted considerable attention recently. Most...

Rahul Radhakrishnan Iyer, et al. ∙

research

∙ 12/13/2019

An Unsupervised Domain-Independent Framework for Automated Detection of Persuasion Tactics in Text

With the increasing growth of social media, people have started relying ...

Rahul Radhakrishnan Iyer, et al. ∙

research

∙ 12/11/2019

Event Outcome Prediction using Sentiment Analysis and Crowd Wisdom in Microblog Feeds

Sentiment Analysis of microblog feeds has attracted considerable interes...

Rahul Radhakrishnan Iyer, et al. ∙

research

∙ 11/20/2019

Deadlock Analysis and Resolution in Multi-Robot Systems: The Two Robot Case

Collision avoidance for multirobot systems is a well studied problem. Re...

Jaskaran Grover, et al. ∙

research

∙ 11/11/2019

MAME : Model-Agnostic Meta-Exploration

Meta-Reinforcement learning approaches aim to develop learning procedure...

Swaminathan Gurumurthy, et al. ∙

research

∙ 10/03/2019

Behavior Mixing with Minimum Global and Subgroup Connectivity Maintenance for Large-Scale Multi-Robot Systems

In many cases the multi-robot systems are desired to execute simultaneou...

Wenhao Luo, et al. ∙

research

∙ 06/04/2019

Learning Transferable Cooperative Behavior in Multi-Agent Teams

While multi-agent interactions can be naturally modeled as a graph, the ...

Akshat Agarwal, et al. ∙

research

∙ 01/21/2019

Active Learning with Gaussian Processes for High Throughput Phenotyping

A looming question that must be solved before robotic plant phenotyping ...

Sumit Kumar, et al. ∙

research

∙ 09/24/2018

Better Safe than Sorry: Evidence Accumulation Allows for Safe Reinforcement Learning

In the real world, agents often have to operate in situations with incom...

Akshat Agarwal, et al. ∙

research

∙ 09/17/2018

Object-sensitive Deep Reinforcement Learning

Deep reinforcement learning has become popular over recent years, showin...

Yuezhang Li, et al. ∙

research

∙ 09/17/2018

Transparency and Explanation in Deep Reinforcement Learning Neural Networks

Autonomous AI systems will be entering human society in the near future ...

Rahul Iyer, et al. ∙

research

∙ 09/15/2018

Towards Better Interpretability in Deep Q-Networks

Deep reinforcement learning techniques have demonstrated superior perfor...

Raghuram Mandyam Annasamy, et al. ∙

research

∙ 09/06/2018

Challenges of Context and Time in Reinforcement Learning: Introducing Space Fortress as a Benchmark

Research in deep reinforcement learning (RL) has coalesced around improv...

Akshat Agarwal, et al. ∙

research

∙ 08/10/2018

Community Regularization of Visually-Grounded Dialog

The task of conducting visually grounded dialog involves learning goal-o...

Akshat Agarwal, et al. ∙

research

∙ 08/10/2018

Mind Your Language: Learning Visually Grounded Dialog in a Multi-Agent Setting

The task of visually grounded dialog involves learning goal-oriented coo...

Akshat Agarwal, et al. ∙

research

∙ 06/12/2018

Combining Model-Free Q-Ensembles and Model-Based Approaches for Informed Exploration

Q-Ensembles are a model-free approach where input images are fed into di...

Sreecharan Sankaranarayanan, et al. ∙

research

∙ 05/17/2018

Learning Time-Sensitive Strategies in Space Fortress

Although there has been remarkable progress and impressive performance o...

Akshat Agarwal, et al. ∙

research

∙ 02/25/2018

Using Information Invariants to Compare Swarm Algorithms and General Multi-Robot Algorithms: A Technical Report

Robotic swarms are decentralized multi-robot systems whose members use l...

Gabriel Arpino, et al. ∙

research

∙ 07/27/2016

Joint Embedding of Hierarchical Categories and Entities for Concept Categorization and Dataless Classification

Due to the lack of structured knowledge applied in learning distributed ...

Yuezhang Li, et al. ∙

research

∙ 05/12/2016

Joint Embeddings of Hierarchical Categories and Entities

Due to the lack of structured knowledge applied in learning distributed ...

Yuezhang Li, et al. ∙

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