Cognitive science
editJ.L. Bermudez - Cognitive Science: An Introduction to the Science of the Mind (2014)
- The prehistory of cognitive science
- The reaction against behaviorism in psychology
- The theory of computation and the idea of an algorithm
- Linguistics and the formal analysis of language
- Information-processing models in psychology
- Connections and points of contact
- The discipline matures: Three milestones
- Language and micro-worlds
- How do mental images represent?
- An interdisciplinary model of vision
- The turn to the brain
- Cognitive systems as functional systems
- The anatomy of the brain and the primary visual pathway
- Extending computational modeling to the brain
- Mapping the stages of lexical processing
- Cognitive science and the integration challenge
- Cognitive science: An interdisciplinary endeavor
- Levels of explanation: The contrast between psychology and neuroscience
- The integration challenge
- Local integration I: Evolutionary psychology and the psychology of reasoning
- Local integration II: Neural activity and the BOLD signal
- Tackling the integration challenge
- Intertheoretic reduction and the integration challenge
- Marr’s tri-level hypothesis and the integration challenge
- Models of mental architecture
- Physical symbol systems and the language of thought
- The physical symbol system hypothesis
- From physical symbol systems to the language of thought
- The Chinese room argument
- Applying the symbolic paradigm
- Expert systems, machine learning, and the heuristic search hypothesis
- ID3: An algorithm for machine learning
- WHISPER: Predicting stability in a block world
- Putting it all together: SHAKEY the robot
- Neural networks and distributed information processing
- Neurally inspired models of information processing
- Single-layer networks and Boolean functions
- Multilayer networks
- Information processing in neural networks: Key features
- Neural network models of cognitive processes
- Language and rules: The challenge for information-processing models
- Language learning in neural networks
- Object permanence and physical reasoning in infancy
- Neural network models of children’s physical reasoning
- Conclusion: The question of levels
- How are cognitive systems organized?
- Architectures for intelligent agents
- Fodor on the modularity of mind
- The massive modularity hypothesis
- Hybrid architectures
- Strategies for brain mapping
- Structure and function in the brain
- Studying cognitive functioning: Techniques from neuroscience
- Combining resources I: The locus of selection problem
- Combining resources II: Networks for attention
- From data to maps: Problems and pitfalls
- A case study: Exploring mindreading
- Pretend play and metarepresentation
- Metarepresentation, autism, and theory of mind
- The mindreading system
- Understanding false belief
- Mindreading as simulation
- The cognitive neuroscience of mindreading
- New horizons: Dynamical systems and situated cognition
- Cognitive science and dynamical systems
- Applying dynamical systems: Two examples from child development
- Situated cognition and biorobotics
- From subsumption architectures to behavior-based robotics
- The cognitive science of consciousness
- The challenge of consciousness: Leibniz's Mill
- Consciousness and information processing: The Knowledge argument
- Information processing without conscious awareness: Some basic data
- So what is consciousness for?
- Two types of consciousness and the hard problem
- The global workspace theory of consciousness
- Conclusion
- Looking ahead: Challenges and applications
- Exploring the connectivity of the brain: The connectome and the BRAIN initiative
- Understanding what the brain is doing when it appears not to be doing anything
- Building artificial brain systems?
- Enhancing education
- Building bridges to economics and the law