Master Award in
Intelligent Agents
Master Award could transfer 20 credits and 50% tuition fees to Master’s programs of UKeU and/or Partner University.

Master Award in Intelligent Agents
The aim of this award is introduces agent-based computing, covering intelligent agent development and interactions in multi-agent environments. It focuses on rational decision-making, negotiation, cooperation, and competition in computational markets. Learners will program a trading agent in Python for a class tournament and explore the role of Large Language Models (LLMs) as agents.
Could transfer 20 credits and 50% tuition fee to the Master of Artificial Intelligence of UKeU.
Learning Outcomes:
1. Understand the foundational principles of agent-based computing.
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1.1 Describe the key motivations for agent-based computing.
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1.2 Explain symbolic, reactive, and practical models of reasoning in intelligent agents.
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1.3 Critically analyse the role of rational decision making in agent systems.
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1.4 Critically evaluate agent-based models for solving complex problems.
2. Understand interactions between agents in multi-agent environments.
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2.1 Describe models of cooperation in agent systems.
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2.2 Explain competitive behaviours in multi-agent environments using game theory.
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2.3 Critically analyse the role of computational markets and auctions in agent-based interactions.
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2.4 Evaluate automated negotiation models in agent systems.
3. Be able to design and implement intelligent agents.
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3.1 Develop structured models of agents in code.
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3.2 Implement agents in a simulated trading environment.
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3.3 Apply practical reasoning strategies in agent-based computational markets.
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3.4 Critically evaluate the performance of agents in competitive settings.
4. Understand advanced applications and ethical considerations in agent-based computing.
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4.1 Describe advanced agent systems used in complex environments.
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4.2 Analyse the effectiveness of intelligent agents in various industries.
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4.3 Evaluate the ethical considerations related to deploying autonomous agents.
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4.4 Determine improvements for implementing agent-based systems in real-world environments.
Topics:
Motivations for Agent-Based Computing
Course Coverage
- Overview of the need for agent-based systems in modern computing.
- Applications of agents in domains such as finance, healthcare, and logistics.
Key Concepts in Agent-Based Systems
Course Coverage:
- Definition and characteristics of intelligent agents (autonomy, reactivity, proactivity, social ability).
- Types of agents: reactive, deliberative, hybrid, and learning agents.
Models of Reasoning
Course Coverage:
- Symbolic Reasoning: Logical deduction and knowledge-based approaches.
- Reactive Reasoning: Rule-based systems and immediate response to stimuli.
- Practical Reasoning: Rational decision-making processes for achieving goals.
Rational Decision-Making Under Uncertainty
Course Coverage:
- Handling uncertainty using probability theory and decision theory.
- Decision trees, Bayesian networks, and Markov decision processes.
Models of Cooperation
Course Coverage:
- Teamwork and Joint Intentions: How agents work together towards shared goals.
- Collaborative Problem-Solving: Techniques for distributed and cooperative problem-solving.
Models of Competitive Behavior
Course Coverage
- Key Concepts in Game Theory: Concepts like Nash Equilibrium, dominant strategies, and payoff matrices.
- Mechanism Design: Crafting mechanisms to encourage desired agent behaviors.
- Competitive Negotiation: Strategies used in competitive environments.
Computational Markets and Auctions
Course Coverage:
- Market-Based Coordination: Using market mechanisms to allocate resources.
- Auction Models: English auctions, Dutch auctions, Vickrey auctions.
- Agent Bidding Strategies: Optimal bidding strategies in online auctions
Automated Negotiation Models
Course Coverage:
- Bilateral Negotiation: Two-agent negotiation for resource allocation.
- Multi-Agent Bargaining: Techniques and strategies for group negotiations.
- Conflict Resolution: Methods to resolve conflicting goals among agents.
Structuring Agent Models
Course Coverage:
- Agent Architectures: Layered, modular, and blackboard-based agent architectures.
- Message Passing and Communication: How agents communicate and share information.
Programming Agents
Course Coverage:
- Python for Agent-Based Systems: Introduction to programming agents in Python (instead of Java) for consistency with other units.
- Design Patterns for Agents: Best practices in coding modular and scalable agents.
- Testing and Debugging Agents: Techniques to evaluate and improve agent behavior.
Simulated Trading Environment
Course Coverage:
- Agent Competitions: Using simulation environments to test trading agents.
- Market Dynamics: How agents adapt and respond to dynamic market conditions.
- Programming Trading Strategies in Python: Implementing reasoning strategies in market scenarios.
Practical Reasoning in Computational Markets
Course Coverage:
- Decision-Making Algorithms: Algorithms for decision-making in auctions and markets.
- Learning from Interactions: How agents learn and optimize strategies in competitive environments.
Advanced Agent Systems
Course Coverage:
- Swarm Intelligence: How simple agents collaborate to achieve complex outcomes.
- Multi-Agent System Architectures: Hierarchical vs. decentralized architectures.
- Real-Time Agent Systems: Applications of agents in high-speed decision-making environments.
Industry Applications of Intelligent Agents
Course Coverage:
- E-Commerce and Financial Trading: How agents are used in automated trading and personalized ecommerce systems.
- Logistics and Supply Chain Management: Agent-based solutions in optimizing logistics networks.
- Healthcare and Smart Systems: Applications of agents in medical diagnosis and smart systems.
- Introduce LLMs as Agents: Exploring how LLMs can be used in decision-making and interaction scenarios.
Ethical Considerations in Agent-Based Computing
Course Coverage:
- Bias and Fairness: Addressing bias in autonomous decision-making.
- Transparency and Accountability: Ensuring transparency in agent decision processes.
- Regulation of Autonomous Agents: Legal implications and policy frameworks for agent-based systems.
Improving Agent-Based Systems
Course Coverage:
- Enhancing Efficiency and Scalability: Techniques to improve agent performance at scale.
- Future Directions: Exploration of emerging trends in agent-based computing, such as hybrid systems and AI-driven agent learning.
- Consider LLM Integration: Discussing potential enhancements with the integration of LLMs into agent-based systems.
Indicative reading list
Core texts:
- Russell, S., & Norvig, P. (2020). Artificial Intelligence: A Modern Approach. Pearson.
- Wooldridge, M. (2009). An Introduction to MultiAgent Systems. Wiley.
- Shoham, Y., & Leyton-Brown, K. (2008). Multiagent Systems: Algorithmic, Game-Theoretic, and Logical Foundations. Cambridge University Press.
- Jennings, N., & Sycara, K. (1998). A Roadmap of Agent Research and Development. International Journal of Autonomous Agents and Multi-Agent Systems.
- Vulkan, N., & Jennings, N. (2000). Efficient Mechanism Design for Agents. Journal of Autonomous Agents and MultiAgent Systems.
Additional reading:
- Artificial Intelligence Journal: www.journals.elsevier.com/artificial-intelligence.
Entry requirements
To enroll The Master Award, the learner must possess:
- Graduated with a Bachelor’s degree from an accredited university or achieved a Level 6 Diploma according to the European Qualifications;
- For a degree from non-recognized universities; The learner should have followed Accreditation of Prior Experiential Learning for Qualifications (APEL.Q) policy of MI Swiss and/or University Partners;
- Learners must be over 21 years old.
English requirements
If a learner is not from a predominantly English-speaking country, proof of English language proficiency must be provided.
- Common European Framework of Reference (CEFR) level B2 or equivalent;
- Or A minimum TOEFL score of 101 or IELTS 5.5; Reading and Writing must be at 5.5 or equivalent.
The UKeU reserves the highest decision-making authority regarding admissions and may accept or reject applicants following a thorough review of each applicant’s profile, ensuring that only those capable of benefiting from the course are admitted. Qualifications from diploma mills or fake universities/institutions will not be accepted by UKeU and/or Partner University.
After graduating with Master Award, learners receive all certified documents from the UKeU.
Certified Documents:
- e-Certificate from the UK eUni Worldwide (UKeU);
- Hard copy certificate from UK eUni Worldwide (UKeU) (Optional);
- Accreditation of Prior Experiential Learning for Qualifications (APEL.Q) certified from UKeU for credit and tuition fee transfer.
Because the course is accredited and recognized, learners can easily use their qualifications in the workplace and enjoy many opportunities for career advancement. In addition, if you wish to pursue a degree from UKeU and/or a Partner University, all credits and 50% paid tuition fees can be transferred.
The UKeU’ Master Award means:
UKeU Master Award is the award at the master level and is equivalent to:
- Level 7 certificate of Regulated Qualifications Framework (RQF) of UK
- Level 10 certificate of Scottish Credit and Qualifications Framework (SCQF)
- Level 7 certificate of Credit and Qualifications Framework (CQFW)
- Level 7 certificate of European Qualifications Framework (EQF)
- Level 9 certificates of the Australian Qualifications Framework (AQF)
- Level 7 certificate of ASEAN Qualifications Reference Framework (AQRF)
- Level 9 certificate of the African Continental Qualifications Framework (ACQF)
Learners can transfer all credits and 50% of their tuition fees when enrolling in UKeU and/or Partner University academic programs if they wish to pursue an academic degree.
Credits transfer:
Learners can transfer 20 credits from the Master Award course when participating in the Master program. Please see the credit transfer policy HERE.
Tuition fee transfer:
When enrolling in the Master program, graduates from the Master Award will receive a fee reduction equal to 50% of the tuition fees paid for the Master Award. Please refer to the tuition fee transfer policy HERE.
The UKeU Micro Degree course allows learners to transfer credits and 50% of their tuition fees toward full degree programs offered by UKeU and/or Partner University. UKeU reserves the right to limit admissions once enrollment exceeds the set quotas.
Apply Policy:
- To participate in the UKeU Micro Degree course, learners need to meet the entry criteria corresponding to each level. Please see the “Entry” tab for more details.
- UKeU will not accept applicants whose entry qualifications are from fake universities or institutions that are not accredited.
- For Master Award courses, if an entry bachelor is unavailable, learners must demonstrate a minimum of 5 years of work experience in the relevant field. Please note that a bachelor’s degree is required for the Master’s program at UKeU and Partner University so that you could study Master Award but could not move to the Master’s program of UKeU and/or Partner University.
- English is not a mandatory entry requirement for Micro Degree course, but candidates need to ensure that English is used in reading documents, listening to lectures, and doing assignments. Applicants should note that English is a mandatory requirement when switching to an academic program at UKeU and Partner University.
Apply Process:
- Step 1: To request a consultation for a course that best suits your needs, please email support@ukeu.uk. Our admissions department will contact you to guide you through the required documentation and the next steps in the application process.
- Step 2: Once your application documents are approved and the application fee is paid, UKeU will issue a Letter of Acceptance (LOA). You will then follow the provided instructions, including payment of the tuition fee.
- Step 3: After the tuition fee is paid, UKeU will issue a confirmation letter, provide your login details for the e-learning system, and send you all relevant documents.
- At this point, you have officially become a UKeU student. Welcome, and enjoy your learning journey!
The UKeU Micro Degree course is fully online, allowing you to study anytime and anywhere. You also have the option to attend live classes with UKeU. Final exams will be uploaded to the system and assessed by the UKeU academic board. Learners are required to submit assignments on time; failure to do so will require payment of a resit fee (with up to two attempts allowed). Continued non-compliance on a third occasion will result in being considered as having discontinued the course, and tuition fees will not be refunded.
Pricing Plans
Take advantage of one of our non-profit professional certified courses with favorable terms for your personal growing carreers.
- Live Class (Optional)
- Full online videos
- e-Books
- Self study contents
- Online tutor videos
- Assignment guide
- e-Certificate
- Hard copy certificate from UKeU and/or Partner Universities
- APEL.Q certified from UKeU for credit and tuition fee transfer
- Deliver hard copy certificate and all certified documents to your home
- Transfer full credits & 50% tuition fees to equivalent academic programs
- Opportunity to get scholarships when becoming Partner Universities' international students
SWISS MICRO CREDENTIAL
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