Representation Edit Distance as a Measure of Novelty. Joshua Alspector. [Paper]
Information-Theoretic Approach to Detect Collusion in Multi-Agent Games. Trevor Bonjour, Vaneet Aggarwal and Bharat Bhargava. [Paper]
Adversarial Creation of a Smart Home Testbed for Novelty Detection. Jarren Briscoe, Assefaw Gebremedhin, Lawrence Holder and Diane Cook. [Paper]
Metacognitive Mechanisms for Novelty Processing: Lessons for AI.
Giedrius Burachas, Scott Grigsby, Bill Ferguson, Jeffrey Krichmar and Rajesh Rao. [Paper]
An Environment Transformation-based Framework for Comparison of Open-World Learning Agents. Matthew Molineaux and Dustin Dannenhauer. [Paper]
An Architecture for Novelty Handling in a Multi-Agent Stochastic Environment: Case Study in Open-World Monopoly. Tung Thai, Ming Shen, Neeraj Varshney, Sriram Gopalakrishnan, Utkarsh Soni, Chitta Baral, Jivko Sinapov and Matthias Scheutz. [Paper]
Anticipatory Thinking Challenges in Open Worlds: Risk Management. Adam Amos-Binks, Dustin Dannenhauer and Leilani Gilpin. [Paper]
Toward Defining Domain Complexity Measure Across Domains. Katarina Doctor, Christine Task, Eric Kildebeck, Mayank Kejriwal, Lawrence Holder and Russell Leong. [Paper]
Open-Learning Framework for Multi-modal Information Retrieval with Weakly Supervised Joint Embedding. Kma Solaiman and Bharat Bhargava. [Paper]
An Integrated Architecture for Online Adaptation to Novelty in Open Worlds using Probabilistic Programming and Novelty-Aware Planning. James Niehaus, Bryan Loyall and Avi Pfeffer. [Paper]
Measuring the Complexity of Domains Used to Evaluate AI Systems. Christopher Pereyda and Lawrence Holder. [Paper]
Decision making without prior knowledge in dynamic environments using Bootstrapped DQN. Bhargav Ganguly, Marina Haliem, Mridul Agarwal, Vaneet Aggarwal and Bharat Bhargava. [Paper]
Runtime Monitoring of Deep Neural Networks Using Top-Down Context Models Inspired by Predictive Processing and Dual Process Theory. Anirban Roy, Adam Cobb, Nathaniel D. Bastian, Brian Jalaian and Susmit Jha. [Paper]
NovGrid: A Flexible Grid World for Evaluating Agent Response to Novelty. Jonathan Balloch, Zhiyu Lin, Mustafa Hussain, Aarun Srinivas, Xiangyu Peng, Julia Kim and Mark Riedl. [Paper]
Self-Initiated Open World Learning for Autonomous AI Agents. Bing Liu, Eric Robertson, Scott Grigsby and Sahisnu Mazumder. [Paper]
Measurement of Novelty Difficulty in Monopoly. Kma Solaiman and Bharat Bhargava. [Paper]
Measuring the Performance of Open-World AI Systems. Vimukthini Pinto, Jochen Renz, Cheng Xue, Peng Zhang, Katarina Doctor and David Aha. [Paper]
Science Birds Novelty: an Open-world Learning Test-bed for Physics Domains. Cheng Xue, Vimukthini Pinto, Peng Zhang, Chathura Gamage, Ekaterina Nikonova and Jochen Renz. [Paper]
Continuous Learning Based Novelty Aware Emotion Recognition System. Mijanur Palash and Bharat Bhargava. [Paper]
Measuring Difficulty of Novelty Reaction. Ekaterina Nikonova, Cheng Xue, Vimukthini Pinto, Chathura Gamage, Peng Zhang and Jochen Renz. [Paper]
Constraints on Theories of Open-World Learning. Pat Langley. [Paper]
L2Explorer: A Lifelong Reinforcement Learning Assessment Environment. Erik C. Johnson, Eric Q. Nguyen, Blake Schreurs, Chigozie S. Ewulum, Chace Ashcraft, Neil M. Fendley,
Megan M. Baker, Alexander New, Gautam K. Vallabha. [Paper]