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Vincent A. Knight

Publications and source records attributed to Vincent A. Knight.

7 recordsLinked to original sources

Introspection Dynamics with Mutation in Additive Games

Cooperation in heterogeneous groups, where individuals differ in resources, productivity, and behavioural responsiveness, underpins collective action across social and biological systems. Introspection dynamics, in which each player compares their payoff to their payoff under the alternative action, provides a natural learning rule for such asymmetric settings. Couto and Pal showed that for additive games, those in which the payoff difference a player evaluates when considering a switch is independent of the other players' actions, the stationary distribution of introspection dynamics is a product measure. We extend this result to introspection dynamics with mutation, where a selected player switches to a random action with some probability independent of payoffs, and with player-specific selection intensities. We show that the product structure is preserved, and we obtain the explicit per-player cooperation probability $p_i=\phi_i(\delta_i)(1-\mu_{i0}-\mu_{i1})+\mu_{i0}$. We consider the heterogeneous public goods game, where $N$ players may differ in their contributions $\alpha_i$, public goods multipliers $r_i$, and selection intensities $\beta_i$; the long-run cooperation probability admits the closed form $$ p_C = \frac{1}{N}\sum_{i=1}^{N} \left[\frac{1-\mu_{i0}-\mu_{i1}}{1+e^{\,\beta_i\alpha_i(1-r_i/N)}}+\mu_{i0}\right]. $$ Several structural consequences follow: a player-specific cooperation threshold at $r_i = N$ under symmetric mutation, a neutral-drift regime in which cooperation is governed entirely by mutation bias, and a mutation-selection balance in which aggregate cooperation is affine in the mutation rate, interpolating between the selection-driven level and neutrality. Mutation also regularises the strong-selection limit, so the closed form holds as $\beta_i\to\infty$, where the mutation-free dynamics degenerate.

cs.GT

A bibliometric study of research topics, collaboration and centrality in the Iterated Prisoner's Dilemma

This manuscript explores the research topics and collaborative behaviour of authors in the field of the Prisoner's Dilemma using topic modeling and a graph theoretic analysis of the co-authorship network. The analysis identified five research topics in the Prisoner's Dilemma which have been relevant over the course of time. These are human subject research, biological studies, strategies, evolutionary dynamics on networks and modeling problems as a Prisoner's Dilemma game. Moreover, the results demonstrated the Prisoner's Dilemma is a field of continued interest, and that it is a collaborative field compared to other game theoretic fields. The co-authorship network suggests that authors are focused on their communities and that not many connections across the communities are made. The most central authors of the network are the authors connected to the main cluster. Through examining the networks of topics, it was uncovered that the main cluster is characterised by the collaboration of authors in a single topic. These findings add to the bibliometrics study in another field and present new questions and avenues of research to understand the reasons for the measured behaviours.

physics.soc-ph

Using a theory of mind to find best responses to memory-one strategies

Memory-one strategies are a set of Iterated Prisoner's Dilemma strategies that have been praised for their mathematical tractability and performance against single opponents. This manuscript investigates best response memory-one strategies with a theory of mind for their opponents. The results add to the literature that has shown that extortionate play is not always optimal by showing that optimal play is often not extortionate. They also provide evidence that memory-one strategies suffer from their limited memory in multi agent interactions and can be out performed by optimised strategies with longer memory. We have developed a theory that has allowed to explore the entire space of memory-one strategies. The framework presented is suitable to study memory-one strategies in the Prisoner's Dilemma, but also in evolutionary processes such as the Moran process, Furthermore, results on the stability of defection in populations of memory-one strategies are also obtained.

cs.GT

Memory depth of finite state machine strategies for the iterated prisoner's dilemma

We develop an efficient algorithm to determine the memory-depth of finite state machines and apply the algorithm to a collection of iterated prisoner's dilemma strategies. The calculation agrees with the memory-depth of other representations of common strategies such as Tit-For-Tat, Tit-For-2-Tats, etc. which are typically represented by lookup tables. Our algorithm allows the complexity of finite state machine based strategies to be characterized on the same footing as memory-n strategies.

cs.GT

Recognising and evaluating the effectiveness of extortion in the Iterated Prisoner's Dilemma

Since the introduction of zero-determinant strategies, extortionate strategies have received considerable interest. While an interesting class of strategies, the definitions of extortionate strategies are algebraically rigid, apply only to memory-one strategies, and require complete knowledge of a strategy (memory-one cooperation probabilities). We describe a method to detect extortionate behaviour from the history of play of a strategy. When applied to a corpus of 204 strategies this method detects extortionate behaviour in well-known extortionate strategies as well others that do not fit the algebraic definition. The highest performing strategies in this corpus are able to exhibit selectively extortionate behavior, cooperating with strong strategies while exploiting weaker strategies, which no memory-one strategy can do. These strategies emerged from an evolutionary selection process and their existence contradicts widely-repeated folklore in the evolutionary game theory literature: complex strategies can be extraordinarily effective, zero-determinant strategies can be outperformed by non-zero determinant strategies, and longer memory strategies are able to outperform short memory strategies. Moreover, while resistance to extortion is critical for the evolution of cooperation, the extortion of weak opponents need not prevent cooperation between stronger opponents, and this adaptability may be crucial to maintaining cooperation in the long run.

cs.GT

Ciw: An open source discrete event simulation library

This paper introduces Ciw, an open source library for conducting discrete event simulations that has been developed in Python. The strengths of the library are illustrated in terms of best practice and reproducibility for computational research. An analysis of Ciw's performance and comparison to several alternative discrete event simulation frameworks is presented.

cs.PF

Higher Spin Alternating Sign Matrices

We define a higher spin alternating sign matrix to be an integer-entry square matrix in which, for a nonnegative integer r, all complete row and column sums are r, and all partial row and column sums extending from each end of the row or column are nonnegative. Such matrices correspond to configurations of spin r/2 statistical mechanical vertex models with domain-wall boundary conditions. The case r=1 gives standard alternating sign matrices, while the case in which all matrix entries are nonnegative gives semimagic squares. We show that the higher spin alternating sign matrices of size n are the integer points of the r-th dilate of an integral convex polytope of dimension (n-1)^2 whose vertices are the standard alternating sign matrices of size n. It then follows that, for fixed n, these matrices are enumerated by an Ehrhart polynomial in r.

math.CO