Types of AI agents
| Institution | Jomo Kenyatta University of Science and Technology |
| Course | Information Technol... |
| Year | 3rd Year |
| Semester | Unknown |
| Posted By | Jeff Odhiambo |
| File Type | |
| Pages | 6 Pages |
| File Size | 160.59 KB |
| Views | 3741 |
| Downloads | 0 |
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Description
AI agents can be classified into several types based on their capabilities and functionalities. Reactive agents respond to their environment without retaining memory or learning from past experiences, executing actions based on predefined rules or current inputs. Deliberative agents, on the other hand, use reasoning and decision-making processes to plan and execute actions, often incorporating learning from past actions. Hybrid agents combine both reactive and deliberative approaches, adapting their behavior depending on the context and task complexity. Moreover, learning agents improve their performance through interaction with the environment, utilizing algorithms like reinforcement learning to adjust their strategies. Finally, autonomous agents operate with a high degree of independence, making decisions and executing tasks without direct human intervention.
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SMA 2371: Partial Differential Equations (Complete Notes, Examples & Solutions) – JKUAT Biostatistics Year 2 Semester 2
These are comprehensive and well-organized lecture notes for SMA 2371: Partial Differential Equations (PDE) offered to BSc. Biostatistics Year 2 Semester 2 students at JKUAT. The notes are neatly arranged from lecture one to the final topics, making them ideal for class learning, revision, CAT preparation, and final examinations.
The notes include detailed explanations, worked examples, step-by-step mathematical derivations, solved exercises, and applications of Partial Differential Equations. Topics covered include:
• Review of basic concepts and partial derivatives
• Jacobians, surfaces and curves in three dimensions
• Simultaneous first-order differential equations
• Methods of solving symmetric differential equations
• Orthogonal trajectories
• Pfaffian differential equations
• Linear first-order partial differential equations
• Formation of PDEs
• Elimination of arbitrary constants and arbitrary functions
• Heat, Wave, Laplace and Poisson equations
• Separation of variables
• Fourier and Laplace Transform methods
• Numerous worked examples, tutorial questions and examination-style problems with solutions.
These notes are suitable for JKUAT students and other university students studying Mathematics, Statistics, Biostatistics, Engineering, Applied Mathematics or related courses. They are an excellent revision resource for CATs and final examinations.
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