Switch to: References

Add citations

You must login to add citations.
  1. AI and Affordances for Mental Action.McClelland Tom - unknown
    To perceive an affordance is to perceive an object or situation as presenting an opportunity for action. The concept of affordances has been taken up across wide range of disciplines, including AI. I explore an interesting extension of the concept of affordances in robotics. Among the affordances that artificial systems have been engineered to detect are affordances to deliberate. In psychology, affordances are typically limited to bodily action, so the it is noteworthy that AI researchers have found it helpful to (...)
    No categories
    Direct download (3 more)  
     
    Export citation  
     
    Bookmark  
  • On How to Build a Moral Machine.Paul Bello & Selmer Bringsjord - 2013 - Topoi 32 (2):251-266.
    Herein we make a plea to machine ethicists for the inclusion of constraints on their theories consistent with empirical data on human moral cognition. As philosophers, we clearly lack widely accepted solutions to issues regarding the existence of free will, the nature of persons and firm conditions on moral agency/patienthood; all of which are indispensable concepts to be deployed by any machine able to make moral judgments. No agreement seems forthcoming on these matters, and we don’t hold out hope for (...)
    Direct download (5 more)  
     
    Export citation  
     
    Bookmark   4 citations  
  • Expanding and Repositioning Cognitive Science.Paul S. Rosenbloom & Kenneth D. Forbus - 2019 - Topics in Cognitive Science 11 (4):918-927.
    Direct download (4 more)  
     
    Export citation  
     
    Bookmark   1 citation  
  • Beyond Single‐Level Accounts: The Role of Cognitive Architectures in Cognitive Scientific Explanation.Richard P. Cooper & David Peebles - 2015 - Topics in Cognitive Science 7 (2):243-258.
    We consider approaches to explanation within the cognitive sciences that begin with Marr's computational level or Marr's implementational level and argue that each is subject to fundamental limitations which impair their ability to provide adequate explanations of cognitive phenomena. For this reason, it is argued, explanation cannot proceed at either level without tight coupling to the algorithmic and representation level. Even at this level, however, we argue that additional constraints relating to the decomposition of the cognitive system into a set (...)
    Direct download (6 more)  
     
    Export citation  
     
    Bookmark   4 citations  
  • The Goal Circuit Model: A Hierarchical Multi‐Route Model of the Acquisition and Control of Routine Sequential Action in Humans.Richard P. Cooper, Nicolas Ruh & Denis Mareschal - 2014 - Cognitive Science 38 (2):244-274.
    Human control of action in routine situations involves a flexible interplay between (a) task-dependent serial ordering constraints; (b) top-down, or intentional, control processes; and (c) bottom-up, or environmentally triggered, affordances. In addition, the interaction between these influences is modulated by learning mechanisms that, over time, appear to reduce the need for top-down control processes while still allowing those processes to intervene at any point if necessary or if desired. We present a model of the acquisition and control of goal-directed action (...)
    Direct download (8 more)  
     
    Export citation  
     
    Bookmark   3 citations  
  • Framing From Experience: Cognitive Processes and Predictions of Risky Choice.Cleotilde Gonzalez & Katja Mehlhorn - 2016 - Cognitive Science 40 (5):1163-1191.
    A framing bias shows risk aversion in problems framed as “gains” and risk seeking in problems framed as “losses,” even when these are objectively equivalent and probabilities and outcomes values are explicitly provided. We test this framing bias in situations where decision makers rely on their own experience, sampling the problem's options and seeing the outcomes before making a choice. In Experiment 1, we replicate the framing bias in description-based decisions and find risk indifference in gains and losses in experience-based (...)
    Direct download (4 more)  
     
    Export citation  
     
    Bookmark   1 citation  
  • Embodied Spatial Cognition.J. Gregory Trafton & Anthony M. Harrison - 2011 - Topics in Cognitive Science 3 (4):686-706.
    We present a spatial system called Specialized Egocentrically Coordinated Spaces embedded in an embodied cognitive architecture (ACT-R Embodied). We show how the spatial system works by modeling two different developmental findings: gaze-following and Level 1 perspective taking. The gaze-following model is based on an experiment by Corkum and Moore (1998), whereas the Level 1 visual perspective-taking model is based on an experiment by Moll and Tomasello (2006). The models run on an embodied robotic system.
    Direct download (6 more)  
     
    Export citation  
     
    Bookmark   1 citation  
  • Extending SME to Handle Large‐Scale Cognitive Modeling.Kenneth D. Forbus, Ronald W. Ferguson, Andrew Lovett & Dedre Gentner - 2017 - Cognitive Science 41 (5):1152-1201.
    Analogy and similarity are central phenomena in human cognition, involved in processes ranging from visual perception to conceptual change. To capture this centrality requires that a model of comparison must be able to integrate with other processes and handle the size and complexity of the representations required by the tasks being modeled. This paper describes extensions to Structure-Mapping Engine since its inception in 1986 that have increased its scope of operation. We first review the basic SME algorithm, describe psychological evidence (...)
    Direct download (4 more)  
     
    Export citation  
     
    Bookmark   10 citations  
  • Representation and Computation in Cognitive Models.Kenneth D. Forbus, Chen Liang & Irina Rabkina - 2017 - Topics in Cognitive Science 9 (3):694-718.
    One of the central issues in cognitive science is the nature of human representations. We argue that symbolic representations are essential for capturing human cognitive capabilities. We start by examining some common misconceptions found in discussions of representations and models. Next we examine evidence that symbolic representations are essential for capturing human cognitive capabilities, drawing on the analogy literature. Then we examine fundamental limitations of feature vectors and other distributed representations that, despite their recent successes on various practical problems, suggest (...)
    Direct download (4 more)  
     
    Export citation  
     
    Bookmark  
  • AI and Cognitive Science: The Past and Next 30 Years.Kenneth D. Forbus - 2010 - Topics in Cognitive Science 2 (3):345-356.
    Artificial Intelligence (AI) is a core area of Cognitive Science, yet today few AI researchers attend the Cognitive Science Society meetings. This essay examines why, how AI has changed over the last 30 years, and some emerging areas of potential interest where AI and the Society can go together in the next 30 years, if they choose.
    Direct download (7 more)  
     
    Export citation  
     
    Bookmark   4 citations