by sfab358 | Jul 26, 2017
Speaker: Simona Fabrizi (Department of Economics, University of Auckland)
Title of the talk: “The Good, The Bad, and The Not So Ugly: Unanimity Voting with Ambiguous Information” based on a joint paper with Addison Pan
Date, Time and Venue: Thursday, 3 August 2017, 2:00-3:00 pm, [Room Change!] now room 260-307 [Business School Building, Level 3]
Abstract: “Collective decision-making leads to poorer quality decisions under the unanimity voting rule than under majority voting especially as the size of the group grows larger, due to the tendency for strategic decision-makers to vote more often against their private information. In jury trials, for instance, it is well-established that strategic voting is responsible for the paradoxical result that the more demanding the hurdle for conviction is, the more likely it is that a jury will convict an innocent defendant. We challenge these findings, by exploring collective decision-making under alternative voting rules when decision-makers face an ambiguous information structure. Specifically, we investigate voting behaviour by ambiguity-averse voters, who are MaxMin Expected Utility Maximizers, demonstrating that unanimity voting is compatible with instances of informative voting, outperforming other voting rules, such as majority voting.”
Everyone welcome!
by sfab358 | May 22, 2017
Speaker: Thomas Pfeiffer (New Zealand Institute for Advanced Study, Massey University)
Title of the talk: “Decision markets in theory, experiment, and practical applications”
Date, Time and Venue: Wednesday, 31 May 2017, 2:00-3:00 pm, 260-307 [Business School Building, Level 3]
What this talk is going to be about, in Thomas’ words: “Knowledge in society is often dispersed, with different individuals holding different pieces of information. Decision markets are novel mechanisms to harness this knowledge for decision-making. They combine scoring rules to reward individuals for accurate forecasts with decision rules to translate aggregated forecasts into decisions. Because of this combination, decision markets can also be viewed as voting mechanisms that tie votes on actions to forecasts of their consequences.
In preparation for a full Marsden proposal on decision markets, I would like to discuss some promising open questions on this topic:
- What are the most interesting theoretical aspects of the proposal?
- What really is the relation between decision markets and voting mechanisms – i.e. what framework in voting theory is best suited to compare decision markets with other voting mechanisms?
- The decision rules in proper decision markets are stochastic – what is the most relevant literature on stochastic voting systems?
- The forecasting functionality of decision markets resembles (to some degree) signalling of candidates intentions prior to an election. Is there theory on campaign promises and voting?
- What are the most interesting aspects in terms of human-subjects experiments
- Proof-of-concept: we currently don’t really have a solid one – what is the best possible experiment for this (e.g. compare to Plott’s XYZ prediction market experiments)?
- What would be a good lab setup/scenario to compare voting and decision markets?
- What are the most relevant implications of such a proposal
- Can decision markets help strengthening evidence-based decision-making in a “post-truth” world?
This is really intended as “sparring” session – I’ll prepare material for about 15 min (max), and would be very grateful for critical feedback, discussion, and pointers to the literature.”
Everyone welcome!
by sfab358 | Mar 6, 2017
Speaker: Jiamou Liu (University of Auckland & CMSS Member)
Title of the talk: “How to Build Your Network? – A Structural Analysis” joint work with Anastasia Moskvina (AUT)
Date, Time and Venue: Wednesday, 5 April 2017, 2:00-3:00 pm, 260-307 [Business School Building, Level 3]
What this talk is going to be about, in Jaimou’s own words: “Creating new ties in a social network facilitates knowledge exchange and affects positional advantage. We study the process of establishing ties between a single node and an existing network in order to reach certain structural goals. We motivate this problem from two perspectives. The first perspective is socialization: we ask how a newcomer can forge relationships with an existing network to place herself at the center. The second perspective is network expansion: we investigate how a network may preserve or reduce its diameter through linking with a new node, hence ensuring small distance between its members. We then extend our discussion to the problem of network integration, which refers to the process of building links between two networks so that they dissolve into a single unified network.”
Everyone welcome!
by sfab358 | Mar 6, 2017
Speaker: Nina Anchugina (PhD Candidate, University of Auckland)
Title of the talk: “A Puzzle of Mixing Discount Functions” joint work with Matthew Ryan (AUT) and Arkadii Slinko (University of Auckland)
Date, Time and Venue: Wednesday, 15 March 2017, 2:00-3:00 pm, 206-202 [Arts 1 Building, Level 2]
What this talk is going to be about, in Nina’s own words: “This talk will introduce the concept of a “discount function” from decision theory, and discuss some results on mixtures of discount functions. These results suggest a puzzle that we are struggling to resolve. Your help is sought!
In decision-theory, intertemporal preferences are modelled using “discount functions”, which attach weights to different points in time at which costs or benefits might be experienced. In reliability theory, “survival functions” describe the probability that a component survives beyond any given point in time. Discount functions and survival functions have similar mathematical properties. If S(t) is a survival function, its “failure rate” is given by -S'(t)/S(t). For discount functions, the analogous quantity is known as the “time preference rate”. For exponential functions, this rate is constant. For hyperbolic functions, which have become popular for modelling intertemporal preferences, this rate is strictly decreasing – a phenomenon known as strictly decreasing impatience (DI). It is well known that mixing – that is, forming convex combinations – of exponentials produces a function that exhibits strictly DI. (The analogous result is also well known in reliability theory.) We study generalisations of this phenomenon, from which a puzzle emerges. For example, we have not been able to prove (or disprove) that mixing an exponential function with a non-exponential function that exhibits DI will always produce a mixture that exhibits strictly DI. Are we missing something, or do these mixtures behave very strangely?”
Everyone welcome!
by sfab358 | Feb 28, 2017
Speaker: Patrick Girard, University of Auckland (Department of Philosophy) and CMSS Member
Title of talk #1: “Ceteris Paribus Preferences”
Date, Time and Venue: Wednesday, 22 March 2017, 2:00-3:00 pm, 206-202 [Arts 1 Building, Level 2]
What talk #1 is going to be about, in Patrick’s own words: “I’m writing a book on Ceteris Paribus Logic. I’m trying to get closure with 10+ years on the topic, which had me doing a log of preference and belief revision logic. I have a chapter on preference logic which at the moment contains no less than 40 definitions of preference! Some are a bit mad, but for the most part they are plausible. As a logician, my goal is to unify them all into a simple preference logic, which is what the book is about, but not what I will bore you with in the talk. Instead, I will get you to realise why one might be so mad as to offer 40 definitions of preferences, and we can discuss if and how it may relate to your own research.”
Title of talk #2: “Inconsistent Logic”
Date, Time and Venue: Wednesday, 29 March 2017, 2:00-3:00 pm, 260-040B [Business School Building, Level 0]
What talk #2 is going to be about, in Patrick’s own words: “Now this is mad! I’m a new-born dialetheist. That’s a philosophical position which says that some contradictions are inevitable. By “inevitable”, we mean that they are true. As non-sensical as it sounds, there’s a lot of research trying to find logics, and mathematics, that can accommodate such madness. Those are called “Paraconsistent Logics” in general. Not all of them need to accept that there are true contradictions, so not all is mad. There are practical motivations for looking at logics that can tolerate inconsistencies. Think about an auto-pilot that needs to save a cabin of free passengers while receiving inconsistent information from it’s various channels. Or think about inconsistencies that people display in their beliefs and preferences, and how those are always idealised away, because we can’t cope with contradiction. Well, maybe we can, if we let in a bit more madness in our logic.”
Everyone welcome!
by dion | May 9, 2016
Speaker: Arkadii Slinko
Affiliation: Department of Mathematics
Title: Growth of dimension in complete simple games
Date: Monday, 16 May 2016
Time: 4:00 pm
Location: Clock Tower 032
Simple games are used to model a wide range of situations from decision making in committees to reliability of systems made from unreliable components and McCulloch-Pitts units in threshold logic. Weighted voting games are a natural and practically important class of simple games, in which each agent is assigned a numerical weight, and a coalition is winning if the sum of weights of agents in that coalition achieves a certain threshold.
The concept of dimension in simple games was introduced by Taylor and Zwicker in 1993 as a measure of remoteness of a given simple game from a weighted game. They demonstrated that the dimension of a simple game can grow exponentially in the number of players. However, the problem of worst-case growth of the dimension in the important class of complete games was left open. Freixas and Puente (2008) showed that complete games of arbitrary dimension exist and, in particular, their examples demonstrate that the worst-case growth of dimension in complete games is at least linear. In this paper, using a novel technique of Kurz and Napel (2015), we demonstrate that the worst-case growth of dimension in complete games is at least polynomial in the number of players. Whether or not it can be exponential remains an open question.
This is a joint paper with Liam O’Dwyer.
Everyone welcome!
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