Published on August 5, 2014
COGNITIVE MODELLING: COGNITIVE MODELLING WHAT ARE WE DOING HERE?: COGNITIVE SCIENCE COGNITIVE MODELING TYPES OF COGNITIVE MODELS FEATURES OF COGNITIVE MODELS STEPS IN COGNITIVE MODELING PRACTICAL USE OF COGNITIVE MODELS ADVANTAGES OF COGNITIVE MODELING SUCCESS STORIES IN THE PAST DIRECTION TO FUTURE CONCLUSION REFERENCES WHAT ARE WE DOING HERE? WHAT IS COGNITIVE SCIENCE ?: “Cognitive science is concerned with understanding the processes that the brain uses to accomplish complex tasks including perceiving, learning, remembering, thinking, predicting, inference, problem solving, decision making, planning, and moving around the environment .” WHAT IS COGNITIVE SCIENCE ? WHAT IS COGNITIVE MODELLING ?: WHAT IS COGNITIVE MODELLING ? COMPUTATIONAL COGNITIVE MODELLIN G COMPUTATIONAL PSHYCOLOGY explores the essence of cognition and various cognitive functionalities developing detailed, process by specifying corresponding computational models of representations, mechanisms, and processes It embodies descriptions of cognition in computer algorithms and programs, based on computer science (Turing 1950). That is, it imputes computational processes onto cognitive functions, and thereby it produces runnable computational models. COGNITIVE MODEL ?: It is a computer program whose behavior is similar in some respect to human behavior from whose development and use we hope to gain insight into human cognition e .g., Categorization model Special model Connectionist model Probabilistic model COGNITIVE MODEL ? BRIEF EXAMPLE :: One highly active area of cognitive modeling is concerned with the question of how we learn to categorize perceptual objects. For example, how does a radiologist learn to categorize whether an x-ray image contains a cancerous tumor, a benign tumor, or no tumor at all? How does a naturalist learn to categorize wild mushrooms as poisonous, edible, or harmless but inedible ? BRIEF EXAMPLE : TYPES OF COGNITIVE MODELS: P rototype model of categorization 1) the learner estimates the central tendency from within each category during training. 2)When a new target stimulus is presented , the similarity of this target to each category prototype is evaluated, and the category with the most similar prototype is chosen of all the examples experienced TYPES OF COGNITIVE MODELS TYPES OF COGNITIVE MODELS: Exemplar model of categorization 1) The learner memorizes all the examples that are experienced from each category during training. 2)When a new target stimulus is presented , the similarity of the target to each stored example is computed for each category , and the category with the greatest total similarity is chosen. TYPES OF COGNITIVE MODELS FEATURES OF COGNITIVE MODELS: 1)Goal is to scientifically explain basic cognitive processes 2) Described in formal (mathematical or computer ) languages 3) Derived from basic principles of cognition FEATURES OF COGNITIVE MODELS BUILDING OF COGNITIVE MODELS: BUILDING OF COGNITIVE MODELS Conceptual theory formal description Theory cognitive model by recasting the verbal statements into mathematical or computer language. Assumptions to complete formal description we have to make additional detailed assumptions in order to complete the model and to generate precise quantitative predictions. Parameter estimation coefficients that are initially unknown need to be estimated from observed data Compare predictions to empirical data models can be compared to each other quantitatively, or we can use a base and saturated model Iterate to constrain models are constrained and modified/extended based on new data This should produce an evolution of models that improve and become more powerful over time ADVANTAGES OF COGNITIVE MODELLING: Is testable Is supported by evidence Helps us understand cognition Is justifiable in some way Is consistent with other aspects of cognition Leads to a unified understanding of cognition Opens up a broad avenue of research ADVANTAGES OF COGNITIVE MODELLING PRACTICAL USE OF COGNITIVE MODELS: Clinical : assessing individual differences between normal and clinical patients Cognitive neuroscience : understanding the function of different brain regions Aging research : change in cognitive function with age Human factors : improving human-machine interactions PRACTICAL USE OF COGNITIVE MODELS PRACTICAL USE OF COGNITIVE MODELS: AI and Robotics : automatic detection tools, handwriting recognition , face recognition, movement in robots, comprehension and document retrieval Social sciences : cognitive and agent-based models of market behavior or social networking PRACTICAL USE OF COGNITIVE MODELS SUCCESS STORIES IN PAST: • T he various models of developmental psychology, including the connectionist models of “ verb past-tense learning ” and the controversies stemming from such models • The tutoring systems based on the ACT-R cognitive architecture , • The model of implicit and explicit learning based on the CLARION cognitive architecture. SUCCESS STORIES IN PAST DIRECTION TO FUTURE ???: 1.There is clearly a need to develop generic models of cognition that are capable of a wide range of cognitive functionalities, to avoid the myopia often resulting from narrowly-scoped research (e.g., in psychology ). 2.Theoretical analysis often lagged behind, often without sufficient effort at validation and theoretical analysis, claims were boldly made about the promise of a certain model or a certain approach. Unfortunately, we have seen quite a few setbacks in the history due to above. DIRECTION TO FUTURE ??? CONCLUSION.. : It is clear that highly significant progress has been made in recent decades in advancing research on cognitive modeling However , it appears that there is still a very long way to go before we fully understand the computational processes of the human mind . Many challenges and issues need to be addressed, including those from designing cognitive architectures, from validation of cognitive models, and from the applications of cognitive models to various domains . As such, it should be considered a crucial field of scientific research, Through the collective effort of this research community, significant advances can be achieved, especially in better understanding the human mind. CONCLUSION.. REFERENCES: Ref  J. R. Anderson, (1983). The Architecture of Cognition. Harvard University Press, Cambridge, MA Ref J. R. Anderson and C. Lebiere, (1998). The Atomic Components of Thought. Lawrence Erlbaum Associates, Mahwah, NJ. Ref J. R. Anderson and C. Lebiere, (2003). The Newell Test for a theory of cognition. Behavioral and Brain Sciences. 26, 587-640. Ref W. Bechtel and G. Graham (eds.), (1998). A Companion to Cognitive Science. Blackwell Publishers, Cambridge, UK. Ref M. Boden, (2006). Mind as Machine: A History of Cognitive Science. Oxford University Press, Oxford, UK. Ref C. Coombs, R. Dawes, and A. Tversky, (1970). Mathematical Psychology. Pren- tice Hall, Englewood Cliffs, NJ. Ref L. Coward and R. Sun, (2004 ). REFERENCES QUESTIONS ??: QUESTIONS ??