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03/28/2023
Adaptive Scaffolding in Block-Based Programming via Synthesizing New Tasks as Pop Quizzes
Block-based programming environments are increasingly used to introduce ...
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03/02/2023
Navigates Like Me: Understanding How People Evaluate Human-Like AI in Video Games
We aim to understand how people assess human likeness in navigation prod...
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02/15/2023
Trust-Region-Free Policy Optimization for Stochastic Policies
Trust Region Policy Optimization (TRPO) is an iterative method that simu...
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01/30/2023
Contrastive Meta-Learning for Partially Observable Few-Shot Learning
Many contrastive and meta-learning approaches learn representations by i...
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01/25/2023
Imitating Human Behaviour with Diffusion Models
Diffusion models have emerged as powerful generative models in the text-...
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11/20/2022
UniMASK: Unified Inference in Sequential Decision Problems
Randomly masking and predicting word tokens has been a successful approa...
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04/28/2022
Towards Flexible Inference in Sequential Decision Problems via Bidirectional Transformers
Randomly masking and predicting word tokens has been a successful approa...
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01/31/2022
Monotonic Improvement Guarantees under Non-stationarity for Decentralized PPO
We present a new monotonic improvement guarantee for optimizing decentra...
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01/31/2022
You May Not Need Ratio Clipping in PPO
Proximal Policy Optimization (PPO) methods learn a policy by iteratively...
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12/11/2021
Deterministic and Discriminative Imitation (D2-Imitation): Revisiting Adversarial Imitation for Sample Efficiency
Sample efficiency is crucial for imitation learning methods to be applic...
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05/20/2021
Navigation Turing Test (NTT): Learning to Evaluate Human-Like Navigation
A key challenge on the path to developing agents that learn complex huma...
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01/26/2021
The MineRL 2020 Competition on Sample Efficient Reinforcement Learning using Human Priors
Although deep reinforcement learning has led to breakthroughs in many di...
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01/14/2021
Evaluating the Robustness of Collaborative Agents
In order for agents trained by deep reinforcement learning to work along...
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01/11/2021
Deep Interactive Bayesian Reinforcement Learning via Meta-Learning
Agents that interact with other agents often do not know a priori what t...
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12/21/2020
Difference Rewards Policy Gradients
Policy gradient methods have become one of the most popular classes of a...
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09/01/2020
"It's Unwieldy and It Takes a Lot of Time." Challenges and Opportunities for Creating Agents in Commercial Games
Game agents such as opponents, non-player characters, and teammates are ...
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07/06/2020
Meta-Learning for Variational Inference
Variational inference (VI) plays an essential role in approximate Bayesi...
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06/15/2020
Analytic Manifold Learning: Unifying and Evaluating Representations for Continuous Control
We address the problem of learning reusable state representations from s...
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06/08/2020
A Comparison of Self-Play Algorithms Under a Generalized Framework
Throughout scientific history, overarching theoretical frameworks have a...
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03/27/2020
Rolling Horizon Evolutionary Algorithms for General Video Game Playing
Game-playing Evolutionary Algorithms, specifically Rolling Horizon Evolu...
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10/28/2019
Generalization in Reinforcement Learning with Selective Noise Injection and Information Bottleneck
The ability for policies to generalize to new environments is key to the...
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03/13/2019
Resource Abstraction for Reinforcement Learning in Multiagent Congestion Problems
Real-world congestion problems (e.g. traffic congestion) are typically v...
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01/23/2019
The Multi-Agent Reinforcement Learning in MalmÖ (MARLÖ) Competition
Learning in multi-agent scenarios is a fruitful research direction, but ...
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08/03/2018
The Text-Based Adventure AI Competition
In 2016 and 2017 at the IEEE Conference on Computational Intelligence in...
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11/17/2017