@article{horton_amant_2017, title={A Partial Contour Similarity-Based Approach to Visual Affordances in Habile Agents}, volume={9}, ISSN={["2379-8939"]}, DOI={10.1109/tcds.2017.2702599}, abstractNote={In a typical tool use task, we can view both the relationship between the agent and the tool and the relationship between the tool and the target in terms of affordances. One set of affordances relates to the ability of the agent to manipulate the tool, while a second set of affordances relates to the ability of the agent to manipulate the target by means of the tool. In both cases, effective tool use is facilitated by the coupling of one object to another: agent-to-tool-to-target. In this paper, we focus on the visual identification of such affordances via contour similarity. Objects with complementary contour segments can fit together, which suggests possible opportunities for effective interactions. We present a system for the identification and evaluation of partial contour-based matches and analyze the system’s behavior. We propose a set of sample tool-use scenarios as part of our analysis. We demonstrate the use of the system in providing guidance to an autonomous robotic agent performing tool selection tasks.}, number={3}, journal={IEEE TRANSACTIONS ON COGNITIVE AND DEVELOPMENTAL SYSTEMS}, author={Horton, Thomas E. and Amant, Robert St.}, year={2017}, month={Sep}, pages={269–280} }
 @article{kennedy_amant_reitter_2016, title={Behavior representation in modeling and simulation: introduction to CMOT special issue: BRiMS 2013}, volume={22}, number={1}, journal={Computational and Mathematical Organization Theory}, author={Kennedy, W. G. and Amant, R. S. and Reitter, D.}, year={2016}, pages={1–3} }
 @article{st amant_roberts_2016, title={Natural interaction for bot detection}, volume={20}, number={4}, journal={IEEE Internet Computing}, author={St Amant, R. and Roberts, D. L.}, year={2016}, pages={69–73} }
 @article{best_kennedy_amant_2015, title={Behavioral representation in modeling and simulation: introduction to CMOT special issue-BRiMS 2012}, volume={21}, number={3}, journal={Computational and Mathematical Organization Theory}, author={Best, B. J. and Kennedy, W. G. and Amant, R. S.}, year={2015}, pages={243–246} }
 @article{amant_2015, title={Natural interaction with visualization systems}, volume={19}, number={6}, journal={IEEE Internet Computing}, author={Amant, R. S.}, year={2015}, pages={60–64} }
 @article{healey_kocherlakota_rao_mehta_amant_2008, title={Visual perception and mixed-initiative interaction for assisted visualization design}, volume={14}, ISSN={["1941-0506"]}, DOI={10.1109/TVCG.2007.70436}, abstractNote={This paper describes the integration of perceptual guidelines from human vision with an AI-based mixed-initiative search strategy. The result is a visualization assistant called ViA, a system that collaborates with its users to identify perceptually salient visualizations for large, multidimensional datasets. ViA applies knowledge of low-level human vision to: (1) evaluate the effectiveness of a particular visualization for a given dataset and analysis tasks; and (2) rapidly direct its search towards new visualizations that are most likely to offer improvements over those seen to date. Context, domain expertise, and a high-level understanding of a dataset are critical to identifying effective visualizations. We apply a mixed-initiative strategy that allows ViA and its users to share their different strengths and continually improve ViA's understanding of a user's preferences. We visualize historical weather conditions to compare ViA's search strategy to exhaustive analysis, simulated annealing, and reactive tabu search, and to measure the improvement provided by mixed-initiative interaction. We also visualize intelligent agents competing in a simulated online auction to evaluate ViA's perceptual guidelines. Results from each study are positive, suggesting that ViA can construct high-quality visualizations for a range of real-world datasets.}, number={2}, journal={IEEE TRANSACTIONS ON VISUALIZATION AND COMPUTER GRAPHICS}, author={Healey, Christopher G. and Kocherlakota, Sarat and Rao, Vivek and Mehta, Reshma and Amant, Robert St.}, year={2008}, pages={396–411} }
 @article{amant_horton_ritter_2007, title={Model-based evaluation of expert cell phone menu interaction}, volume={14}, number={1}, journal={ACM Transactions on Computer-human Interaction}, author={Amant, R. S. and Horton, T. E. and Ritter, F. E.}, year={2007} }
 @article{amant_young_2001, title={Interface agents in model world environments}, volume={22}, number={4}, journal={AI Magazine}, author={Amant, R. S. and Young, R. M.}, year={2001}, pages={95–107} }