Master Award in
Intelligent Agents
Master Award could transfer 20 credits and full tuition fees to Master’s programs by SIMI and University Partners.
Master Award in Intelligent Agents
This unit 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 full tuition fee to the Master of Artificial Intelligence of SIMI Swiss and University Partners.
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 SIMI and/or University Partners.
- Learners must be over 21 years old.
The SIMI Swiss reserves the highest decision-making power for admission whether to accept or not accept after a specific review of each candidate’s profile to ensure that they can comprehend and gain benefits when participating. For the fake university or diploma mills, University Partners shall not be accepted.
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 6.5; Reading and Writing must be at 6.5 or equivalent.
After graduating with Master Award, students receive all certified documents from the SIMI Swiss.
Certified Documents:
- e-Certificate from the Swiss Information and Management Institute (SIMI Swiss).
- Hard copy certificate from the Swiss Information and Management Institute (SIMI Swiss) – Optional.
- Accreditation of Prior Experiential Learning for Qualifications (APEL.Q) certified from SIMI Swiss for credit and tuition fee transfer.
Because the program is accredited and recognized, students can easily use certified in the working environment and have many opportunities for career advancement. In addition, in case if you want to study for a SIMI degree or university partner degree, students can convert all credits and the full paid tuition fee when participating in the program University Partners.
The SIMI Swiss’ Master Award means:
SIMI Swiss Master Award is the award at the master level and is equivalent to:
- Level 7 certificate of Regulated Qualification 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)
Students can convert all credits and the full tuition fee when participating in the SIMI Swiss and/or University Partners academic programs if they want to study for an academic degree.
Credits transfer:
Learners can accumulate 20 credits from the Master Award program when participating in the Master of Artificial Intelligence. Please see the credit transfer policy HERE
Tuition fee transfer:
When participating in the Master of Artificial Intelligence program, students who have graduated 1 Master Award will receive a discount of full tuition fee which you paid. Please see the tuition fee transfer HERE
The SIMI Swiss micro-credential program allows for the transfer of credits and tuition fees into full degree programs from SIMI Swiss and/or its university partners. SIMI Swiss reserves the right to limit admissions once the number of students exceeds the quotas.
Apply Policy:
- To participate in the SIMI Swiss micro-credential program, students need to meet the entry criteria corresponding to each level. Please see the “Entry” tab for more details.
- SIMI Swiss will not accept applicants if their entry qualifications are from diploma mill universities or schools/universities that are not accredited.
- For Master Award programs, if an entry bachelor is unavailable, students 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 SIMI Swiss and University Partners so that you could study Master Award but could not move to the Master’s program of SIMI and University Partners.
- English is not a mandatory entry requirement for short course programs, but candidates need to ensure that English is used in reading documents, listening to lectures, and doing assignments. Candidates should note that English is a mandatory requirement when switching to an academic program at SIMI Swiss and University Partners.
Apply Process:
- Choose the program that suits your requirements. Note that applicants without a university degree will not be able to participate in the program at Master’s level, and applicants without a Master’s degree will not be able to participate in the program at the Doctoral level.
- Email your application to support@simiswiss.ch with all the required documents. You could download the application form here.
- Our admission department will contact you and guide you through further processes if the registration documents need to be supplemented.
- SIMI Swiss will issue the Letter of Acceptant (LOA). You wil proceed to the next steps according to the instructions and pay tuition fee.
- SIMI Swiss will issue a student confirmation letter, login account to the e-learning system and related documents.
- You have become an official SIMI Swiss student and enjoy your study journey.
The SIMI Swiss micro-credential program is fully online, allowing you to study anytime, anywhere. You have the option to attend live classes with SIMI Swiss. The final exam will be uploaded to the system and evaluated by the academic panel of SIMI Swiss. Students must submit assignments on time; failure to do so will result in the student being considered to have discontinued the program.
Pricing Plans
Take advantage of one of our non-profit professional certified programs with favorable terms for your personal growing carreers.
- Live Class (Option)
- Full online videos
- e-Books
- Self study contents
- Online tutor videos
- Assignment guide
- e-Certificate
- Hard copy certificate
- Accreditation of Prior Experiential Learning for Qualifications (APEL.Q) certified from University Partners for credit and tuition fee transfer
- Accreditation & Recognition certified from University Partners
- Deliver hard copy certificate and all certified documents to your home
- Transfer full credits & tuition fees to equivalent academic programs
- Get more support tuition fees and scholarships when becoming University Partners' international students
- (*) In the event that you receive a scholarship or discount, the fee you should transfer is the amount you actually paid.
SWISS MICRO CREDENTIAL
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