ECON1000 Game Theory Presentation

The GTP is a ‘take-home’ exercise with a set of tasks to do. The GTP is based on Lecture Topics: L1 and L2. You will have twenty (21) days to complete the GTP on your own.

• Assessment brief available on Blackboard (Bb): 13th August 2021, 11:59pm.
• Clarifications of and indirect guidance on GTP in L2(a) and L2(b) tutorials: Week 4 of August 16th to 20th; Week 5 of August 23rd to 27th.
• Due date/time of GTP: Word Document to Turnitin by Week 6 Friday 3rd of September, 11:59pm (Perth, AWST).

GTP consists of two parts:

Part 1 is on the first issue, worth 20 marks

Part 2 is on the second issue, worth 10 marks

This game theory presentation (GTP) in S2 2021 relates to two separate issues. Your objective is to apply game theory to these issues:

The first issue is about your hypothetical driving behaviour towards an artificial intelligence (AI) robotic agent vs. one of your fellow humans on the road. How would you respond in say a merging-traffic situation, would you treat an AI self- driving car any different to a human driver? Would you take advantage of and exploit a friendly/benevolent AI agent and not feel guilty about it? Similarly, would you be inclined to take advantage of a friendly/non-aggressive human driver or act kind to them? What would you do?

The second issue is about climate change. In this unit, you will become familiar with the collective action problem of climate change seen as a coordination game between two major economic powerhouses, China and the US. An idea here is that the environment is a public good that calls for collective action and cooperation amongst its citizens—yet when a nation acts self-interestedly there is an incentive to ‘free ride’ on the climate change mitigation efforts of others. How is the climate change game being played out in recent times? Is it a global free-rider problem?

A general guide on what the marker is looking for in the GTP is recalling the tutor-student discussions in the workshop sessions: WAQ_2 of Module L1; WAQ_2 of Module L2(a); and WAQ_2 of Module L2(b). Your tutor as an exemplar would have gone through the process on how best to explain the payoff matrices, and so on.

To do the GTP, complete the tasks set out in this assessment by yourself, and then submit it to Turnitin by the due date: include your Full Name and Student ID as a title in the Word document when submitting your work (see Assessments tab on Bb).

Note, the word count is a suggested maximum. The main thing is that you just answer the question and have sufficient explanations. For more information, see PDF on Bb, “Marking Guidance and FAQs for GTP S2 2021”.

A.  Assessment Tasks

Part 1 – 20 Marks

Read the following news article:

https://www.sciencedaily.com/releases/2021/06/210610135534.htm

This article is based on the following peer-reviewed paper by Karpus, Jurgis, Adrian Krüger, Julia Tovar Verba, Bahador Bahrami, Ophelia Deroy (2021), “This Algorithm exploitation: Humans are keen to exploit benevolent AI”, iScience, Vol. 24 (6) June 25, https://doi.org/10.1016/j.isci.2021.102679. The expectation is that you should only need to focus your attention on reading the introduction and discussion sections of Karpus’ et al. (2021) paper.

Your game theory tasks for Part 1 are as follows:

In 2 separately played games, you are to construct a relevant payoff matrix (in numbers only) for each game based on the main conclusions from the paper.

In the first game, to help you construct the payoff matrix, here are the key parameters:

• There are two players – player ‘a’ you, and player ‘b’ AI robotic agent.
• There are two strategies – cooperate or
• Each strategy has an associated

Think of this as a simultaneously played game: this is a game played once and is repeated more than once, yet the rules, players, and payoffs are the same each time.

In the second game, to help you construct the payoff matrix, here are the key parameters:

• There are two players – player ‘a’ you, and player ‘b’ another
• There are two strategies – cooperate or
• Each strategy has an associated

Think of this as a sequentially played game: one player (chosen randomly) chooses a strategy first, and then the second moves. Assume players are acting rationally.

In each game, you will need to work out what the associated numerical (hypothetical) payoffs are. Explain in words each quadrant and any specific outcome you come across.

In your analysis, discuss the role of preferences amongst the players and how this affects the allocation. Provide some comments on the differences on fairness between the two separate games.