Katia Sycara

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Carnegie Mellon University

Research Professor, Robotics and holder (part time) of the Sixth Century Chair in computing Science, University of Aberdeen UK. Director of the Advanced Agent-Robotics Technology Lab.

Natural Emergence of Heterogeneous Strategies in Artificially Intelligent Competitive Teams

Multi agent strategies in mixed cooperative-competitive environments can...
07/06/2020 ∙ by Ankur Deka, et al. ∙ 0 ∙ share

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MA 3 : Model Agnostic Adversarial Augmentation for Few Shot learning

Despite the recent developments in vision-related problems using deep ne...
04/10/2020 ∙ by Rohit Jena, et al. ∙ 0 ∙ share

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Loss-annealed GAIL for sample efficient and stable Imitation Learning

Imitation learning is the problem of learning a policy from an expert po...
01/21/2020 ∙ by Rohit Jena, et al. ∙ 8 ∙ share

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Simultaneous Identification of Tweet Purpose and Position

Tweet classification has attracted considerable attention recently. Most...
12/24/2019 ∙ by Rahul Radhakrishnan Iyer, et al. ∙ 0 ∙ share

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

With the increasing growth of social media, people have started relying ...
12/13/2019 ∙ by Rahul Radhakrishnan Iyer, et al. ∙ 17 ∙ share

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

Sentiment Analysis of microblog feeds has attracted considerable interes...
12/11/2019 ∙ by Rahul Radhakrishnan Iyer, et al. ∙ 11 ∙ share

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

Collision avoidance for multirobot systems is a well studied problem. Re...
11/20/2019 ∙ by Jaskaran Grover, et al. ∙ 0 ∙ share

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MAME : Model-Agnostic Meta-Exploration

Meta-Reinforcement learning approaches aim to develop learning procedure...
11/11/2019 ∙ by Swaminathan Gurumurthy, et al. ∙ 20 ∙ share

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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...
10/03/2019 ∙ by Wenhao Luo, et al. ∙ 0 ∙ share

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Learning Transferable Cooperative Behavior in Multi-Agent Teams

While multi-agent interactions can be naturally modeled as a graph, the ...
06/04/2019 ∙ by Akshat Agarwal, et al. ∙ 0 ∙ share

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Active Learning with Gaussian Processes for High Throughput Phenotyping

A looming question that must be solved before robotic plant phenotyping ...
01/21/2019 ∙ by Sumit Kumar, et al. ∙ 0 ∙ share

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

In the real world, agents often have to operate in situations with incom...
09/24/2018 ∙ by Akshat Agarwal, et al. ∙ 0 ∙ share

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Object-sensitive Deep Reinforcement Learning

Deep reinforcement learning has become popular over recent years, showin...
09/17/2018 ∙ by Yuezhang Li, et al. ∙ 2 ∙ share

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Transparency and Explanation in Deep Reinforcement Learning Neural Networks

Autonomous AI systems will be entering human society in the near future ...
09/17/2018 ∙ by Rahul Iyer, et al. ∙ 0 ∙ share

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Towards Better Interpretability in Deep Q-Networks

Deep reinforcement learning techniques have demonstrated superior perfor...
09/15/2018 ∙ by Raghuram Mandyam Annasamy, et al. ∙ 18 ∙ share

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

Research in deep reinforcement learning (RL) has coalesced around improv...
09/06/2018 ∙ by Akshat Agarwal, et al. ∙ 0 ∙ share

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Community Regularization of Visually-Grounded Dialog

The task of conducting visually grounded dialog involves learning goal-o...
08/10/2018 ∙ by Akshat Agarwal, et al. ∙ 0 ∙ share

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

The task of visually grounded dialog involves learning goal-oriented coo...
08/10/2018 ∙ by Akshat Agarwal, et al. ∙ 0 ∙ share

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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...
06/12/2018 ∙ by Sreecharan Sankaranarayanan, et al. ∙ 0 ∙ share

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Learning Time-Sensitive Strategies in Space Fortress

Although there has been remarkable progress and impressive performance o...
05/17/2018 ∙ by Akshat Agarwal, et al. ∙ 0 ∙ share

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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...
02/25/2018 ∙ by Gabriel Arpino, et al. ∙ 0 ∙ share

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

Due to the lack of structured knowledge applied in learning distributed ...
07/27/2016 ∙ by Yuezhang Li, et al. ∙ 0 ∙ share

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Joint Embeddings of Hierarchical Categories and Entities

Due to the lack of structured knowledge applied in learning distributed ...
05/12/2016 ∙ by Yuezhang Li, et al. ∙ 0 ∙ share

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Katia Sycara

Featured Co-authors

Zhiting Hu

Mike Lewis

Changliu Liu

Tian Tian

Rahul Radhakrishnan Iyer

Sumit Kumar

Yuezhang Li

Akshat Agarwal

Shirsendu Sukanta Halder

Swaminathan Gurumurthy

Rahul Iyer

Natural Emergence of Heterogeneous Strategies in Artificially Intelligent Competitive Teams

MA 3 : Model Agnostic Adversarial Augmentation for Few Shot learning

Loss-annealed GAIL for sample efficient and stable Imitation Learning

Simultaneous Identification of Tweet Purpose and Position

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

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

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

MAME : Model-Agnostic Meta-Exploration

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

Learning Transferable Cooperative Behavior in Multi-Agent Teams

Active Learning with Gaussian Processes for High Throughput Phenotyping

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

Object-sensitive Deep Reinforcement Learning

Transparency and Explanation in Deep Reinforcement Learning Neural Networks

Towards Better Interpretability in Deep Q-Networks

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

Community Regularization of Visually-Grounded Dialog

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

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

Learning Time-Sensitive Strategies in Space Fortress

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

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

Joint Embeddings of Hierarchical Categories and Entities