- AP503 Working Collaboratively with Healthcare Professionals Assignment Brief 2026
- AP502 Professional Standards within Aesthetic Practice Assignment Brief 2026
- AP501 Legal and Regulatory Requirements in Aesthetic Practice Assignment Brief 2026
- 7FNCE015W Global Banking and Lending Assessment 1, 2026 | UOW
- AP301 Skincare to Support Aesthetic Procedures Assignment Brief 2026
- CO403 Laser Core of Knowledge (J/651/6011) Assignment Brief 2026
- CO402 Client Consultation for Aesthetic Procedures Assignment Brief 2026
- CO401 Health, Safety and Hygiene for Aesthetic Procedures Assignment Brief 2026
- BMG563 Leadership and Change Assessment Brief 2026 | Ulster University
- AP415 Skin Rejuvenation using Dermaplaning (F/650/3429) Assignment Brief 2026
- AP413 Hair Reduction using Laser, Light and Energy-Based Devices Assignment Brief 2026
- AP412 Skin Rejuvenation Using Laser, Light and Energy-Based Devices (A/650/3427) Assignment Brief 2026
- AP414 Skin Rejuvenation using Electrotherapy Assignment Brief 2026
- AP411 Skin Rejuvenation using Mesotherapy Assignment Brief 2026
- AP409 Skin Rejuvenation Using Microneedling Assignment Brief 2026
- AP408 Skin Rejuvenation Using a Plasma Device Assignment Brief 2026
- AP407 Micropigmentation Techniques to Enhance Lips Assignment Brief 2026
- AP406 Micropigmentation Techniques to Enhance Eyes Assignment Brief 2026
- HSC305 Understanding Diabetes Care Assignment Brief 2026
- Qualifi Level 3 HSC304 Person-Centred Care Assignment Brief 2026
OTHM Level 7 Intelligent Agents (K/651/3600) Assignment Brief 2026
| University | OTHM Qualifications |
| Subject | Intelligent Agents (K/651/3600) |
Intelligent Agents Assignment Brief
| Qualification | OTHM Level 7 Diploma in Artificial Intelligence (610/4802/1) |
| Unit Reference Code | K/651/3600 |
| Unit Name | Intelligent Agents |
| Credit | 20 |
| GLH | 100 |
| TQT | 200 |
| Mandatory / Optional | Mandatory |
| Unit Grading Type | Pass / Fail |
Assignment Aim
This unit provides a broad introduction to the rapidly expanding field of agent-based computing. Learners will explore the key concepts and models involved in developing individual intelligent agents and their interactions in a multi-agent environment. A strong focus in this unit is placed on rational decision-making under uncertainty, automated negotiation, cooperation, and competitive behaviour in computational markets such as online auctions. Learners will gain practical experience by programming a trading agent in Python, which will compete in a class tournament within a simulated trading environment. The unit may also touch upon Large Language Models (LLMs) as agents to understand their growing role in intelligent systems.
Learning Outcomes and Assessment Criteria
| Learning Outcome – The learner will: | Assessment Criteria – The learner can: |
| 1. Understand the foundational principles of agent-based computing. | 1.1 Describe the key motivations for agent-based computing.
1.2 Explain symbolic, reactive, and practical models of reasoning in intelligent agents. 1.3 Critically analyse the role of rational decision making in agent systems. 1.4 Critically evaluate agent-based models for solving complex problems. |
| 2. Understand interactions between agents in multi-agent environments. | 2.1 Describe models of cooperation in agent systems.
2.2 Explain competitive behaviours in multi-agent environments using game theory. 2.3 Critically analyse the role of computational markets and auctions in agent-based interactions. 2.4 Evaluate automated negotiation models in agent systems. |
| 3. Be able to design and implement intelligent agents. | 3.1 Develop structured models of agents in code. 3.2 Implement agents in a simulated trading environment.
3.3 Apply practical reasoning strategies in agent-based computational markets. 3.4 Critically evaluate the performance of agents in competitive settings. |
| 4. Understand advanced applications and ethical considerations in agent-based computing. | 4.1 Describe advanced agent systems used in complex environments.
4.2 Analyse the effectiveness of intelligent agents in various industries. 4.3 Evaluate the ethical considerations related to deploying autonomous agents 4.4 Determine improvements for implementing agent-based systems in real-world environments. |
Assessment
To achieve a ‘pass’ for this unit, learners must provide evidence to demonstrate that they have fulfilled all the learning outcomes and meet the standards specified by all assessment criteria.
| Learning Outcomes to be met | Assessment Criteria to be covered | Assessment type | Word count (approx. length) |
| LO1-LO3 | All AC’s under LO1 – LO3 | Trading Agent Programming and Class Tournament | Python-based project +
Performance evaluation (1000-word report) |
| LO4 | All ACs under LO4 | Final Coursework (Essay + Reflection) | 3500 words |
Get Your OTHM Level 7 Intelligent Agents (K/651/3600) Assignment Written by Experts
Short deadlines can make the intelligent agents (K/651/3600) assignment stressful, especially when you must code a trading agent, assess its competitive performance and write the final essay. Students looking to help with university assignment can choose Students Assignment Help UK for expert-written intelligent agents assignment help. Browse our OTHM assignment samples or order online coursework help for a solution shaped around your course requirements.
Answer
