CS255 Artificial Intelligence
Throughout the 2020-21 academic year, we will be adapting the way we teach and assess modules in line with government guidance on social distancing and other protective measures in response to Coronavirus. Teaching will vary between online and on-campus delivery through the year, and you should read the additional information linked on the right hand side of this page for details of how we anticipate this will work. The contact hours shown in the module information below are superseded by the additional information. You can find out more about the University’s overall response to Coronavirus at: https://warwick.ac.uk/coronavirus.
CS255-15 Artificial Intelligence
Introductory description
This module will introduce the foundational concepts in artificial intelligence and knowledge-based systems.
This module is only available to students in the second year of their degree and is not available as an unusual option to students in other years of study.
Module aims
This module will introduce the foundational concepts in artificial intelligence and knowledge-based systems. Specifically, it will provide a broad coverage of search, planning, adversarial search (games), constraint satisfaction problem solving, reinforcement learning, rational and logical agency, knowledge representation techniques, and Bayesian approaches to artificial intelligence.
Outline syllabus
This is an indicative module outline only to give an indication of the sort of topics that may be covered. Actual sessions held may differ.
- Introduction
- Rational Agents
- Agent Architectures and Hierarchical Control
- Uninformed Search
- Informed Search
- Constraint Satisfaction Problems
- Local Search
- Adversarial Search
- Planning
- Knowledge Representation
- Bayesian Al
- Reinforcement Learning
- Deliberative and Reactive Architectures
- Agent Cooperation
Learning outcomes
By the end of the module, students should be able to:
- - Develop an appreciation for Knowledge Based Systems, Intelligent Agents and their architectures
- - Understand a wide variety of knowledge representation and artificial intelligence approaches to planning
- - Understand various methods for search (uninformed and informed), planning and reinforcement learning
- - Understand various methods for representing and reasoning under uncertainty.
Indicative reading list
Please see Talis Aspire link for most up to date list.
View reading list on Talis Aspire
Subject specific skills
develop an appreciation for Knowledge Based Systems, Intelligent Agents and their architectures,
understand a wide variety of knowledge representation and artificial intelligence approaches to planning,
understand various methods for search (uninformed and informed), planning and reinforcement learning, and
understand various methods for representing and reasoning under uncertainty.
Transferable skills
Programming
Communication skills (written)
Problem solving
Critical thinking
Study time
| Type | Required |
|---|---|
| Lectures | 30 sessions of 1 hour (20%) |
| Seminars | 7 sessions of 1 hour (5%) |
| Private study | 113 hours (75%) |
| Total | 150 hours |
Private study description
Required reading (as identified in lectures)
Background reading
Exercise sheets
Revision
Coursework
Costs
No further costs have been identified for this module.
You do not need to pass all assessment components to pass the module.
Students can register for this module without taking any assessment.
Assessment group D3
| Weighting | Study time | |
|---|---|---|
| Coursework | 20% | |
| CS255 exam | 80% | |
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~Platforms - AEP
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Assessment group R
| Weighting | Study time | |
|---|---|---|
| CS255 resit exam | 100% | |
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CS255 resit exam ~Platforms - AEP |
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Feedback on assessment
Mark and written feedback returned via Tabula.
Courses
This module is Optional for:
- Year 2 of UCSA-I1N1 Undergraduate Computer Science with Business Studies
- Year 2 of UCSA-G406 Undergraduate Computer Systems Engineering
- Year 2 of UCSA-G408 Undergraduate Computer Systems Engineering
- Year 2 of UCSA-G5N1 Undergraduate Computer and Management Sciences
- Year 2 of USTA-G302 Undergraduate Data Science
- Year 2 of USTA-G304 Undergraduate Data Science (MSci)
This module is Option list A for:
- Year 2 of UCSA-G400 BSc Computing Systems
- Year 2 of UCSA-G402 MEng Computing Systems
- Year 2 of UCSA-G500 Undergraduate Computer Science
- Year 2 of UCSA-G503 Undergraduate Computer Science MEng
This module is Option list B for:
- Year 2 of UCSA-GN51 Undergraduate Computer and Business Studies
- Year 2 of UCSA-G4G1 Undergraduate Discrete Mathematics
- Year 2 of UCSA-G4G3 Undergraduate Discrete Mathematics
This module is Option list C for:
- Year 2 of UCSA-G5N1 Undergraduate Computer and Management Sciences
Further Information
Term 1
15 CATS (7.5 ECTS)
Note: This module is only available to students in the second year of their degree and is not available as an unusual option to students in other years of study.