Unit-5: Neuro Dynamics Neuro Dynamics : Dynamical Systems, Stability of Equilibrium States, Attractors, Neuro Dynamical Models, Manipulation of Attractors as a Recurrent Network Paradigm Hopfield Models – Hopfield Models, restricted boltzmen machine. Neuro Dynamics refers to the study of how the state of a neural network evolves over time according to specific update rules or differential equations. It focuses on the temporal behaviour , stability , and trajectory of neural activations until the network reaches a steady state or attractor . In simple words: Neuro Dynamics = Time-evolution of neuron states + stability of the network’s behaviour. It treats the neural network as a dynamical system rather than a static input–output model. What is Neuro Dynamics? In Neural Networks, Neuro Dynamics describes: How neuron activations change step-by-step or continuously How the network moves in its state space How it settles into stable patterns ...
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Unit 3: Solving Problems by Searching & Uninformed Search Algorithm
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Unit-3: Solving Problems by Searching & Uninformed Search Algorithms Solving Problems by Searching: Problem Solving Agents: Well-Defined Problems and Solutions, Formulating problems, Example Problems: Toys Problems, Real-World Problems, Searching for Solutions, Uninformed Search Algorithms: BFS, Uniform-Cost Search, DFS, Depth Limited Search, Iterative Deepening, and Bidirectional Search. Solving Problems by Searching: In AI, Searching is the basic technique used for solving problems. Whenever an agent (robot, software, etc.) doesn't know what to do immediately, it can search through possible actions and their outcomes to find a solution path . Search = exploring possible actions until the goal is reached. Problem Solving Agents: A Problem-Solving Agent is a type of intelligent agent designed to find sequences of actions that lead to desirable outcomes (i.e., solving a problem). It operates by: Formulatin...