--- title: AI & Computational Modeling description: AI and computational modeling uses computer simulations to study human cognition and behavior. You will understand how to build algorithmic models of mental processes, analyze neural networks, and use machine learning to simulate decision-making, perception, and language acquisition. category: social-sciences subcategory: cognitive-science difficulty: beginner, intermediate, advanced url: /subject/ai-and-computational-modeling --- # AI & Computational Modeling AI and computational modeling uses computer simulations to study human cognition and behavior. You will understand how to build algorithmic models of mental processes, analyze neural networks, and use machine learning to simulate decision-making, perception, and language acquisition. ## Available Resources 1 Videos • 1 Books • 2 Courses • 3 Websites ## Courses ### 1. Model-Based Machine Learning Kevin Murphy's textbook Probabilistic Machine Learning: An Introduction, free as a draft PDF. It covers probability, statistics, information and decision theory, linear models, deep networks and causal discovery within one probabilistic framework, with Python code for most figures. **Difficulty:** Intermediate | **Price:** Free **Link:** https://probml.github.io/pml-book/book1.html **Tags:** probabilistic-modeling, machine-learning, bayesian-inference, deep-learning, textbook ### 2. Computational Neuroscience **Author:** Adrienne Fairhall, Rajesh Rao University of Washington course on how neurons and networks represent and process information, covering neural encoding and decoding, information theory, single-neuron biophysical models, synaptic plasticity and network learning. Learners can build and interpret quantitative models of neural computation through programming exercises. **Difficulty:** Intermediate | **Language:** English | **Price:** Free **Link:** https://www.coursera.org/learn/computational-neuroscience **Tags:** computational-neuroscience, neural-coding, information-theory, neuron-models, synaptic-plasticity ## Videos ### 1. 3Blue1Brown - Neural Networks series Grant Sanderson's 3Blue1Brown channel offers visually intuitive and mathematically rigorous explanations of complex topics. His series on neural networks is particularly praised for making the core concepts, like backpropagation, understandable through animated visuals. **Difficulty:** Beginner | **Language:** English | **Price:** Free **Link:** https://www.youtube.com/playlist?list=PLW_xnxm7jEso **Tags:** neural-networks, backpropagation, gradient-descent, deep-learning, visual-explanation ## Websites ### 1. neuromatch.io Neuromatch.io is the hub for Neuromatch’s online neuroscience education and community resources, offering free materials for learning computational neuroscience—courses, lectures, tutorials, and code notebooks—along with information about events and the Neuromatch Academy. **Difficulty:** Intermediate | **Language:** English | **Price:** Free **Link:** https://neuromatch.io **Tags:** websites, humanities-social-sciences, psychology ### 2. netlogo.org NetLogo.org is the official site for the NetLogo agent-based modeling environment. It provides the NetLogo software, a vast Models Library, tutorials, documentation, and resources to learn, build, and run agent-based simulations. **Difficulty:** Intermediate | **Language:** English | **Price:** Free **Link:** https://netlogo.org **Tags:** websites, humanities-social-sciences, cognitive-science ### 3. act-r.psy.cmu.edu Official hub for ACT-R, the Carnegie Mellon cognitive architecture for modeling human cognition. It offers tutorials, documentation, software downloads, example models, and research publications for building and evaluating cognitive models. **Difficulty:** Intermediate | **Language:** English | **Price:** Free **Link:** https://act-r.psy.cmu.edu **Tags:** websites, humanities-social-sciences, cognitive-science ## Books ### 1. Parallel Distributed Processing **Author:** David E. Rumelhart, James L. McClelland, PDP Research Group Volume 1 of the 1986 Rumelhart and McClelland collection that revived neural network research, presenting the parallel distributed processing framework, distributed representations, and the backpropagation chapter, alongside connectionist models of perception, memory and schemata. **Difficulty:** Intermediate | **Language:** English | **Price:** Paid **Link:** https://www.amazon.com/dp/026268053X?tag=edmonddante07-20 **Tags:** books, humanities-social-sciences, cognitive-science --- *This content is part of Dantes.io - Your Treasure Map to Knowledge* *Curated by humans at Dantes.io. Personal study use welcome; republishing this curation requires permission (team@dantes.io).* View this page online: https://dantes.io/subject/ai-and-computational-modeling