Katalog Tshirt Enzo terkini 2015. Merangkumi tshirt lengan pendek, tshirt lengan panjang, tshirt muslimah, cap yang lebih cantik dan berkualiti dengan harga yang sangat berpatutan. Semua pelanggan saya sukakannya. DIJAMIN PUAS HATI
1. The document proposes modifications to the ACT-R cognitive architecture to model mental rotation and imagery using explicit spatial representations and computational geometry processes.
2. It describes two mental rotation strategies - holistic and piecemeal - and presents productions that instantiate each strategy using the modified ACT-R representations and processes.
3. The models are able to qualitatively replicate the response time patterns found in human mental rotation experiments using different stimuli to encourage holistic or piecemeal strategies.
1. The document discusses multiple representations in cognitive architectures, including symbolic and visual/imagery-based representations.
2. It reviews past and current attempts to model visual mental imagery in cognitive architectures using array-based and retinotopic representations.
3. The concept of multi-representation cognition is introduced, where problems can be solved using different mental representations, like mathematical/symbolic vs. visual imagery representations, each with their own advantages.
Katalog Tshirt Enzo terkini 2015. Merangkumi tshirt lengan pendek, tshirt lengan panjang, tshirt muslimah, cap yang lebih cantik dan berkualiti dengan harga yang sangat berpatutan. Semua pelanggan saya sukakannya. DIJAMIN PUAS HATI
1. The document proposes modifications to the ACT-R cognitive architecture to model mental rotation and imagery using explicit spatial representations and computational geometry processes.
2. It describes two mental rotation strategies - holistic and piecemeal - and presents productions that instantiate each strategy using the modified ACT-R representations and processes.
3. The models are able to qualitatively replicate the response time patterns found in human mental rotation experiments using different stimuli to encourage holistic or piecemeal strategies.
1. The document discusses multiple representations in cognitive architectures, including symbolic and visual/imagery-based representations.
2. It reviews past and current attempts to model visual mental imagery in cognitive architectures using array-based and retinotopic representations.
3. The concept of multi-representation cognition is introduced, where problems can be solved using different mental representations, like mathematical/symbolic vs. visual imagery representations, each with their own advantages.
Multiple representations and visual mental imagery in artificial cognitive sy...University of Huddersfield
1) The document discusses multiple representations in artificial cognitive systems, including both external representations like diagrams and internal mental representations like visual mental imagery.
2) It presents examples of how problems can be solved using either a mathematical/propositional representation or a visual/imagery-based representation.
3) Leading cognitive architectures are discussed in terms of how they have begun to incorporate multiple representations, with some exploring non-symbolic, array-based representations to model processes involved in visual mental imagery.
1. The document discusses multiple representations in human cognition and cognitive architectures. It focuses on visual mental imagery and how cognitive models can incorporate different representational formats like diagrams, images, and symbols.
2. Current cognitive architectures mainly use symbolic representations which are insufficient for modeling visual imagery. A few models employ array-based representations to better capture spatial reasoning and imagery abilities.
3. For cognitive models to exhibit human-level intelligence, they need mechanisms for flexibly selecting and coordinating multiple internal and external representations.
Two methods are described for optimizing cognitive model parameters: differential evolution (DE) and high-throughput computing with HTCondor. DE is a genetic algorithm that uses a population of models to explore the parameter space in parallel. It is well-suited for models with few parameters or short run times. HTCondor allows running a population of models over a computer network, making it suitable for larger, more complex models or simulating many participants. Examples of using each method with an ACT-R paired associate model are provided.
Machine Learning, Artificial General Intelligence, and Robots with Human MindsUniversity of Huddersfield
The document discusses different types of artificial intelligence and outlines a new project to install the ACT-R cognitive architecture onto a NAO robot to create a robot with human-level general intelligence and flexible goal-directed behavior through embodied cognition, perception, motor skills, communication, learning and adaptation. The goal is to gain insights into building advanced autonomous agents by modeling key aspects of human cognition and intelligence.
This document summarizes two studies on how people orient themselves using maps in urban environments. The first study found that people often make errors in orientation when relying on highly visually salient objects that are not clear on the map, ignoring important ground-level cues, or misjudging object distances. The second study found that strong 2D ground cues on maps can improve accuracy, but the presence of a salient 3D landmark can confuse people and reduce accuracy. A process model of map-based orientation is proposed based on these findings. The studies have implications for how to design maps to best support orientation.
Graph comprehension model talk, Birkbeck and Toulouse Le Mirail, February 2012University of Huddersfield
The document describes a computational model of graph comprehension built within the ACT-R cognitive architecture. The model simulates how experts and novices interpret interaction graphs by encoding spatial relationships between plotted points and applying prior knowledge about graphical representations. It identifies variables, encodes distances between points symbolically, and recognizes patterns to describe effects. While focused on expert-level understanding, the model represents an initial step toward accounting for individual differences and a broader range of graph types.
Diagrammatic Cognition: Discovery and Design workshop, Humboldt University, B...University of Huddersfield
This workshop is designed to integrate a wide variety of cognitive science perspectives on the roles diagrams play in cognition, addressing various ways in which people design and use diagrams to spatialize thought and make it public, to work through ideas and clarify thinking, to reduce working memory load, to communicate ideas to others, to promote collaborative work by providing an external representation that can be pointed to and animated by gestures and collectively revised. The morning session (talks by Tversky, Healey, and Kirsh) will focus on creating and diagrams and using them to coordinate various activities, the afternoon (talks by Bechtel, Cheng, and Hegarty) will examine uses of diagrams in science. Both session will also include blitz talks presenting one major idea; scholars who would like to present blitz talks should contact the organizer.
http://mechanism.ucsd.edu/diagrammaticcognition.html
A cognitive architecture-based modelling approach to understanding biases in ...University of Huddersfield
Title: "A cognitive architecture-based modelling approach to
understanding biases in visualisation behaviour". A talk given at the "Dealing with Cognitive Biases in Visualisations (DECISIVe 2014) workshop at IEEE VIS, Paris, November 2014.
Title: "Sources of bias when working with visualisations". Introduction to the "Dealing with Cognitive Biases in Visualisations (DECISIVe 2014) workshop at IEEE VIS, Paris, November 2014.
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