In many real-world route planning and search tasks, humans must solve a combinatorial optimizatio... more In many real-world route planning and search tasks, humans must solve a combinatorial optimization problem that holds many similarities to the Euclidean Traveling Salesman Problem (TSP). The problem spaces used in real-world tasks differ most starkly from traditional TSP in terms of optimization criteria - Whereas the traditional TSP asks participants to connect all of the nodes to produce the solution that minimizes overall path length, real-world search tasks are often conducted with the goal of minimizing the duration of time required to find the target (i.e., the average distance between nodes). Traditional modeling approaches to TSP assume that humans solve these problems using intrinsic characteristics of the brain and perceptual system (e.g., hierarchical structure in the visual system). A consequence of these approaches is that they are not robust to strategic changes in the aforementioned optimization criteria during path planning. To investigate performance in these tasks,...
Page 1. AFRL-RH-WP-TR-2011-DELINEATING CULTURAL MODELS Shane T. Mueller Applied Research Associat... more Page 1. AFRL-RH-WP-TR-2011-DELINEATING CULTURAL MODELS Shane T. Mueller Applied Research Associates, Inc. 1750 Commerce Center Boulevard, North Fairborn OH 45324-6362 AUGUST 2010 Final Report Distribution ...
Alexei V. Samsonovich (chair) Krasnow Institute for Advanced Study George Mason University Fairfa... more Alexei V. Samsonovich (chair) Krasnow Institute for Advanced Study George Mason University Fairfax, VA 22030-4444, USA [email protected] ... Antonio Chella (Università di Palermo, Italy) Ben Goertzel (Novamente/AGIRI, USA) Richard H. Granger (Dartmouth College, USA) Laurent Itti (University of Southern California, USA) Deepak Khosla (HRL Laboratories, USA) Shane T. Mueller (Klein Associates Division/ARA, USA) David C. Noelle (University of California Merced, USA) Murray Shanahan (Imperial College London, UK)
THE SKILLS REQUIRED TO SOLVE CROSSWORD PUZZLES INVOLVE TWO IMPORTANT ASPECTS OF LEXICAL MEMORY: s... more THE SKILLS REQUIRED TO SOLVE CROSSWORD PUZZLES INVOLVE TWO IMPORTANT ASPECTS OF LEXICAL MEMORY: semantic information in the form of clues that indicate the meaning of the answer, and orthographic patterns that constrain the possibilities but may also provide hints to possible answers. Mueller and Thanasuan (2013) proposed a model accounting for the simple memory access processes involved in solving individual crossword clues, but expert solvers also bring additional skills and strategies to bear on solving complete puzzles. In this paper, we developed an computational model of crossword solving that incorporates strategic and other factors, and is capable of solving crossword puzzles in a human-like fashion, in order to understand the complete set of skills needed to solve a crossword puzzle. We compare our models to human expert and novice solvers to investigate how different strategic and structural factors in crossword play impact overall performance. Results reveal that expert c...
We describe the Bivalent Shape Task (BST), software using the Psychology Experiment Building Lang... more We describe the Bivalent Shape Task (BST), software using the Psychology Experiment Building Language (PEBL), for testing of cognitive interference and the ability to suppress interference. The test is available via the GNU Public License, Version 3 (GPLv3), is freely modifiable, and has been tested on both children and adults and found to provide a simple and fast non-verbal measure of cognitive interference and suppression that requires no reading.
In the present study, we used a synthetic task environment representing an aerial wilderness sear... more In the present study, we used a synthetic task environment representing an aerial wilderness search and rescue task to test and validate neurocomputational models of the human hippocampus. Participants completed two tasks: a search task, in which they searched a wooded area for multiple targets, and a route choice task, in which they searched high and low density probability regions, parametrically varied by relative distance, for a single target. The decision task was designed to examine participant evaluation of cost versus expected reward. We compared participant behavior during this task with (1) an optimal model, which makes decisions based on a cost to reward ratio, and (2) a neurocomputational model based on hippocampal architecture, which generates activation from probability weighted reward sites. We discuss initial results using this paradigm and the bases by which we will model performance during unmanned aerial search for multiple targets.
Solving crossword puzzles involves a memory-based decision process using two simultaneous cue typ... more Solving crossword puzzles involves a memory-based decision process using two simultaneous cue types: semantic and orthographic. To understand this type of constrained decision process, we have developed a cognitive model of these processes that we demonstrate can be trained to solve puzzle questions as well or better than most humans. The model enables us to test how humans perform the search process, by examining alternative accounts of knowledge access. We conclude that the most reasonable explanation for human crossword play is a dual-route process, by which each of two routes are searched independently and consecutively, with the fluency of the semantic route being the most important factor distinguishing novice and expert players. We conclude by discussing general implications for expertise as a recognitional decision process.
... Phonological Similarity Effects in Working Memory Shane T. Mueller, Travis Seymour, Adam Kraw... more ... Phonological Similarity Effects in Working Memory Shane T. Mueller, Travis Seymour, Adam Krawitz, David E. Kieras, and David E. Meyer ... Verbal WM Baddeley, Thomson, and Buchanan (1975) claimed that serial recall accuracy depends on the articulatory duration ...
2010 International Symposium on Collaborative Technologies and Systems, CTS 2010, 2010
Today operators in complex task domains such as aviation, process control, medicine and the milit... more Today operators in complex task domains such as aviation, process control, medicine and the military must work closely with automation to achieve levels of performance that would be impossible to reach independently. To maximize the full benefit of this man-machine relationship operator trust must be appropriately calibrated with the trustworthiness of the system. Misalignment of trust with the automation's capabilities
The hippocampus has long been thought to be critical in learning and representing the cognitive m... more The hippocampus has long been thought to be critical in learning and representing the cognitive map, and thus support functions such as search, pathfinding and route planning. This work aims to demonstrate the utility of hippocampus-based neural networks in modeling human search task behavior. Human solutions to pathfinding problems are generally fast but approximate, in contrast to traditional AI approaches. In this paper, we report data on a human search task, and then examine a set of models, based upon the structure of the hippocampus, which use a goal scent mechanism similar to the optimal pathfinding algorithms used in artificial intelligence systems. We compare five distinct search models, and conclude that a goal scent model driven by multiple goals spread throughout the search space provides the best and most accurate account of the human data. This research suggests a convergence in traditional AI and biologically-inspired approaches to pathfinding that may be mutually beneficial. ª 2013 Published by Elsevier B.V. 2212-683X/$ -see front matter ª 2013 Published by Elsevier B.V. http://dx.(S.T. Mueller). Biologically Inspired Cognitive Architectures (2013) 5, 94-111 Av ai la bl e at w w w . s c i e n c e d i r e c t . c o m j o u r n a l h o m e p a g e : w w w . e l s e v i e r . c o m / l o c a t e / b i c a
In many real-world route planning and search tasks, humans must solve a combinatorial optimizatio... more In many real-world route planning and search tasks, humans must solve a combinatorial optimization problem that holds many similarities to the Euclidean Traveling Salesman Problem (TSP). The problem spaces used in real-world tasks differ most starkly from traditional TSP in terms of optimization criteria - Whereas the traditional TSP asks participants to connect all of the nodes to produce the solution that minimizes overall path length, real-world search tasks are often conducted with the goal of minimizing the duration of time required to find the target (i.e., the average distance between nodes). Traditional modeling approaches to TSP assume that humans solve these problems using intrinsic characteristics of the brain and perceptual system (e.g., hierarchical structure in the visual system). A consequence of these approaches is that they are not robust to strategic changes in the aforementioned optimization criteria during path planning. To investigate performance in these tasks,...
Page 1. AFRL-RH-WP-TR-2011-DELINEATING CULTURAL MODELS Shane T. Mueller Applied Research Associat... more Page 1. AFRL-RH-WP-TR-2011-DELINEATING CULTURAL MODELS Shane T. Mueller Applied Research Associates, Inc. 1750 Commerce Center Boulevard, North Fairborn OH 45324-6362 AUGUST 2010 Final Report Distribution ...
Alexei V. Samsonovich (chair) Krasnow Institute for Advanced Study George Mason University Fairfa... more Alexei V. Samsonovich (chair) Krasnow Institute for Advanced Study George Mason University Fairfax, VA 22030-4444, USA [email protected] ... Antonio Chella (Università di Palermo, Italy) Ben Goertzel (Novamente/AGIRI, USA) Richard H. Granger (Dartmouth College, USA) Laurent Itti (University of Southern California, USA) Deepak Khosla (HRL Laboratories, USA) Shane T. Mueller (Klein Associates Division/ARA, USA) David C. Noelle (University of California Merced, USA) Murray Shanahan (Imperial College London, UK)
THE SKILLS REQUIRED TO SOLVE CROSSWORD PUZZLES INVOLVE TWO IMPORTANT ASPECTS OF LEXICAL MEMORY: s... more THE SKILLS REQUIRED TO SOLVE CROSSWORD PUZZLES INVOLVE TWO IMPORTANT ASPECTS OF LEXICAL MEMORY: semantic information in the form of clues that indicate the meaning of the answer, and orthographic patterns that constrain the possibilities but may also provide hints to possible answers. Mueller and Thanasuan (2013) proposed a model accounting for the simple memory access processes involved in solving individual crossword clues, but expert solvers also bring additional skills and strategies to bear on solving complete puzzles. In this paper, we developed an computational model of crossword solving that incorporates strategic and other factors, and is capable of solving crossword puzzles in a human-like fashion, in order to understand the complete set of skills needed to solve a crossword puzzle. We compare our models to human expert and novice solvers to investigate how different strategic and structural factors in crossword play impact overall performance. Results reveal that expert c...
We describe the Bivalent Shape Task (BST), software using the Psychology Experiment Building Lang... more We describe the Bivalent Shape Task (BST), software using the Psychology Experiment Building Language (PEBL), for testing of cognitive interference and the ability to suppress interference. The test is available via the GNU Public License, Version 3 (GPLv3), is freely modifiable, and has been tested on both children and adults and found to provide a simple and fast non-verbal measure of cognitive interference and suppression that requires no reading.
In the present study, we used a synthetic task environment representing an aerial wilderness sear... more In the present study, we used a synthetic task environment representing an aerial wilderness search and rescue task to test and validate neurocomputational models of the human hippocampus. Participants completed two tasks: a search task, in which they searched a wooded area for multiple targets, and a route choice task, in which they searched high and low density probability regions, parametrically varied by relative distance, for a single target. The decision task was designed to examine participant evaluation of cost versus expected reward. We compared participant behavior during this task with (1) an optimal model, which makes decisions based on a cost to reward ratio, and (2) a neurocomputational model based on hippocampal architecture, which generates activation from probability weighted reward sites. We discuss initial results using this paradigm and the bases by which we will model performance during unmanned aerial search for multiple targets.
Solving crossword puzzles involves a memory-based decision process using two simultaneous cue typ... more Solving crossword puzzles involves a memory-based decision process using two simultaneous cue types: semantic and orthographic. To understand this type of constrained decision process, we have developed a cognitive model of these processes that we demonstrate can be trained to solve puzzle questions as well or better than most humans. The model enables us to test how humans perform the search process, by examining alternative accounts of knowledge access. We conclude that the most reasonable explanation for human crossword play is a dual-route process, by which each of two routes are searched independently and consecutively, with the fluency of the semantic route being the most important factor distinguishing novice and expert players. We conclude by discussing general implications for expertise as a recognitional decision process.
... Phonological Similarity Effects in Working Memory Shane T. Mueller, Travis Seymour, Adam Kraw... more ... Phonological Similarity Effects in Working Memory Shane T. Mueller, Travis Seymour, Adam Krawitz, David E. Kieras, and David E. Meyer ... Verbal WM Baddeley, Thomson, and Buchanan (1975) claimed that serial recall accuracy depends on the articulatory duration ...
2010 International Symposium on Collaborative Technologies and Systems, CTS 2010, 2010
Today operators in complex task domains such as aviation, process control, medicine and the milit... more Today operators in complex task domains such as aviation, process control, medicine and the military must work closely with automation to achieve levels of performance that would be impossible to reach independently. To maximize the full benefit of this man-machine relationship operator trust must be appropriately calibrated with the trustworthiness of the system. Misalignment of trust with the automation's capabilities
The hippocampus has long been thought to be critical in learning and representing the cognitive m... more The hippocampus has long been thought to be critical in learning and representing the cognitive map, and thus support functions such as search, pathfinding and route planning. This work aims to demonstrate the utility of hippocampus-based neural networks in modeling human search task behavior. Human solutions to pathfinding problems are generally fast but approximate, in contrast to traditional AI approaches. In this paper, we report data on a human search task, and then examine a set of models, based upon the structure of the hippocampus, which use a goal scent mechanism similar to the optimal pathfinding algorithms used in artificial intelligence systems. We compare five distinct search models, and conclude that a goal scent model driven by multiple goals spread throughout the search space provides the best and most accurate account of the human data. This research suggests a convergence in traditional AI and biologically-inspired approaches to pathfinding that may be mutually beneficial. ª 2013 Published by Elsevier B.V. 2212-683X/$ -see front matter ª 2013 Published by Elsevier B.V. http://dx.(S.T. Mueller). Biologically Inspired Cognitive Architectures (2013) 5, 94-111 Av ai la bl e at w w w . s c i e n c e d i r e c t . c o m j o u r n a l h o m e p a g e : w w w . e l s e v i e r . c o m / l o c a t e / b i c a
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