Image scoring in ad-hoc networks : an investigation on realistic settings

Encouraging cooperation in distributed Multi-Agent Systems (MAS) remains an open problem. Emergent application domains such as Mobile Ad-hoc Networks (MANETs) are characterised by constraints including sparse connectivity and a lack of direct interaction history. Image scoring, a simple model of reputation proposed by Nowak and Sigmund, exhibits low space and time complexity and promotes cooperation through indirect reciprocity, in which an agent can expect cooperation in the future without repeat interactions with the same partners. The low overheads of image scoring make it a promising technique for ad-hoc networking domains. However, the original investigation of Nowak and Sigmund is limited in that it (i) used a simple idealised setting, (ii) did not consider the effects of incomplete information on the mechanism’s efficacy, and (iii) did not consider the impact of the network topology connecting agents. We address these limitations by investigating more realistic values for the number of interactions agents engage in, and show that incomplete information can cause significant errors in decision making. As the proportion of incorrect decisions rises, the efficacy of image scoring falls and selfishness becomes more dominant. We evaluate image scoring on three different connection topologies: (i) completely connected, which closely approximates Nowak and Sigmund’s original setup, (ii) random, with each pair of nodes connected with a constant probability, and (iii) scale-free, which is known to model a number of real world environments including MANETs

Supporting cooperation and coordination in open multi-agent systems

Cooperation and coordination between agents are fundamental processes for increasing aggregate and individual benefit in open Multi-Agent Systems (MAS). The increased ubiquity, size, and complexity of open MAS in the modern world has prompted significant research interest in the mechanisms that underlie cooperative and coordinated behaviour. In open MAS, in which agents join and leave freely, we can assume the following properties: (i) there are no centralised authorities, (ii) agent authority is uniform, (iii) agents may be heterogeneously owned and designed, and may consequently have con icting intentions and inconsistent capabilities, and (iv) agents are constrained in interactions by a complex connecting network topology. Developing mechanisms to support cooperative and coordinated behaviour that remain effective under these assumptions remains an open research problem. Two of the major mechanisms by which cooperative and coordinated behaviour can be achieved are (i) trust and reputation, and (ii) norms and conventions. Trust and reputation, which support cooperative and coordinated behaviour through notions of reciprocity, are effective in protecting agents from malicious or selfish individuals, but their capabilities can be affected by a lack of information about potential partners and the impact of the underlying network structure. Regarding conventions and norms, there are still a wide variety of open research problems, including: (i) manipulating which convention or norm a population adopts, (ii) how to exploit knowledge of the underlying network structure to improve mechanism efficacy, and (iii) how conventions might be manipulated in the middle and latter stages of their lifecycle, when they have become established and stable. In this thesis, we address these issues and propose a number of techniques and theoretical advancements that help ensure the robustness and efficiency of these mechanisms in the context of open MAS, and demonstrate new techniques for manipulating convention emergence in large, distributed populations. Specfically, we (i) show that gossiping of reputation information can mitigate the detrimental effects of incomplete information on trust and reputation and reduce the impact of network structure, (ii) propose a new model of conventions that accounts for limitations in existing theories, (iii) show how to manipulate convention emergence using small groups of agents inserted by interested parties, (iv) demonstrate how to learn which locations in a network have the greatest capacity to in uence which convention a population adopts, and (v) show how conventions can be manipulated in the middle and latter stages of the convention lifecycle

Gossip for social control in natural and artificial societies

In this work we propose a theory of gossip as a means for social control. Exercising social control roughly means to isolate and to punish cheaters. However, punishment is costly and it inevitably implies the problem of second-order cooperation. Moving from a cognitive model of gossip, we report data from ethnographic studies and agent-based simulations to support our claim that gossip reduces the costs of social control without lowering its efficacy

Sustainable Cooperation in Peer-To-Peer Networks

Traditionally, peer-to-peer systems have relied on altruism and reciprocity. Although incentive-based models have gained prominence in new-generation peer-to-peer systems, it is essential to recognize the continued importance of cooperative principles in achieving performance, fairness, and correctness. The lack of this acknowledgment has paved the way for selfish peers to gain unfair advantages in these systems. As such, we address the challenge of selfish peers by devising a mechanism to reward sustained cooperation. Instead of relying on global accountability mechanisms, we propose a protocol that naturally aggregates local evaluations of cooperation. Traditional mechanisms are often vulnerable to Sybil and misreporting attacks. However, our approach overcomes these issues by limiting the benefits selfish peers can gain without incurring any cost. The viability of our algorithm is proven with a deployment to 27,259 Internet users and a realistic simulation of a blockchain gossip protocol. We show that our protocol sustains cooperation even in the presence of a majority of selfish peers while incurring only negligible overhead

Evolution of Social Networks Among American Female Adolescents

This study delves into the evolution of social networks incorporating both elements of Rational Choice Theory and Feminist Theory inside a Social Network analysis. Simulated data was generated by modeling American female adolescents as an instantiation of a more general set of theoretical ideas about the formation of gendered relational patterns. This study uses the methodology of Computer Simulation to explore micro to macro mechanisms and account for how individual social actions aggregate to generate macro-level network structures. This research examines generative mechanisms and explores under what conditions some characteristics of gendered network structures emerge and are maintained through time. Three AVI files (movies of simulation demos) and a JAR (Java ARchive) of the JAVA code are also included

Reputation

In this chapter, the role of reputation as a distributed instrument for social order is addressed. A short review of the state of the art will show the role of reputation in promoting (a) social control in cooperative contexts - like social groups and subgroups - and (b) partner selection in competitive contexts, like (e-) markets and industrial districts. In the initial section, current mechanisms of reputation - be they applied to electronic markets or MAS - will be shown to have poor theoretical backgrounds, missing almost completely the cognitive and social properties of the phenomenon under study. In the rest of the chapter a social cognitive model of reputation developed in the last decade by some of the authors will be presented. Its simulation-based applications to the theoretical study of norm-abiding behaviour, partner selection and to the refinement and improvement of current reputation mechanisms will be discussed. Final remarks and ideas for future research will conclude the chapte

Optimising Cooperative Spectrum Sensing in Cognitive Radio Networks Using Interference Alignment and Space-Time Coding

In this thesis, the process of optimizing Cooperative Spectrum Sensing in Cognitive Radio has been investigated in fast-fading environments where simulation results have shown that its performance is limited by the Probability of Reporting Errors. By proposing a transmit diversity scheme using Differential space-time block codes (D-STBC) where channel state information (CSI) is not required and regarding multiple pairs of Cognitive Radios (CR’s) with single antennas as a virtual MIMO antenna arrays in multiple clusters, Differential space-time coding is applied for the purpose of decision reporting over Rayleigh channels. Both Hard and Soft combination schemes were investigated at the fusion center to reveal performance advantages for Hard combination schemes due to their minimal bandwidth requirements and simplistic implementation. The simulations results show that this optimization process achieves full transmit diversity, albeit with slight performance degradation in terms of power with improvements in performance when compared to conventional Cooperative Spectrum Sensing over non-ideal reporting channels. Further research carried out in this thesis shows performance deficits of Cooperative Spectrum Sensing due to interference on sensing channels of Cognitive Radio. Interference Alignment (IA) being a revolutionary wireless transmission strategy that reduces the impact of interference seems well suited as a strategy that can be used to optimize the performance of Cooperative Spectrum Sensing. The idea of IA is to coordinate multiple transmitters so that their mutual interference aligns at their receivers, facilitating simple interference cancellation techniques. Since its inception, research efforts have primarily been focused on verifying IA’s ability to achieve the maximum degrees of freedom (an approximation of sum capacity), developing algorithms for determining alignment solutions and designing transmission strategies that relax the need for perfect alignment but yield better performance. With the increased deployment of wireless services, CR’s ability to opportunistically sense and access the unused licensed frequency spectrum, without causing harmful interference to the licensed users becomes increasingly diminished, making the concept of introducing IA in CR a very attractive proposition. For a multiuser multiple-input–multiple-output (MIMO) overlay CR network, a space-time opportunistic IA (ST-OIA) technique has been proposed that allows spectrum sharing between a single primary user (PU) and multiple secondary users (SU) while ensuring zero interference to the PUs. With local CSI available at both the transmitters and receivers of SUs, the PU employs a space-time WF (STWF) algorithm to optimize its transmission and in the process, frees up unused eigenmodes that can be exploited by the SU. STWF achieves higher performance than other WF algorithms at low to moderate signal-to-noise ratio (SNR) regimes, which makes it ideal for implementation in CR networks. The SUs align their transmitted signals in such a way their interference impairs only the PU’s unused eigenmodes. For the multiple SUs to further exploit the benefits of Cooperative Spectrum Sensing, it was shown in this thesis that IA would only work when a set of conditions were met. The first condition ensures that the SUs satisfy a zero interference constraint at the PU’s receiver by designing their post-processing matrices such that they are orthogonal to the received signal from the PU link. The second condition ensures a zero interference constraint at both the PU and SUs receivers i.e. the constraint ensures that no interference from the SU transmitters is present at the output of the post-processing matrices of its unintended receivers. The third condition caters for the multiple SUs scenario to ensure interference from multiple SUs are aligned along unused eigenmodes. The SU system is assumed to employ a time division multiple access (TDMA) system such that the Principle of Reciprocity is employed towards optimizing the SUs transmission rates. Since aligning multiple SU transmissions at the PU is always limited by availability of spatial dimensions as well as typical user loads, the third condition proposes a user selection algorithm by the fusion centre (FC), where the SUs are grouped into clusters based on their numbers (i.e. two SUs per cluster) and their proximity to the FC, so that they can be aligned at each PU-Rx. This converts the cognitive IA problem into an unconstrained standard IA problem for a general cognitive system. Given the fact that the optimal power allocation algorithms used to optimize the SUs transmission rates turns out to be an optimal beamformer with multiple eigenbeams, this work initially proposes combining the diversity gain property of STBC, the zero-forcing function of IA and beamforming to optimize the SUs transmission rates. However, this solution requires availability of CSI, and to eliminate the need for this, this work then combines the D-STBC scheme with optimal IA precoders (consisting of beamforming and zero-forcing) to maximize the SUs data rates

The rise and fall of cooperation through reputation and group polarization

Humans exhibit a remarkable capacity for cooperation among genetically unrelated individuals. Yet, human cooperation is neither universal, nor stable. Instead, cooperation is often bounded to members of particular groups, and such groups endogenously form or break apart. Cooperation networks are parochial and under constant reconfiguration. Here, we demonstrate how parochial cooperation networks endogenously emerge as a consequence of simple reputation heuristics people may use when deciding to cooperate or defect. These reputation heuristics, such as “a friend of a friend is a friend” and “the enemy of a friend is an enemy” further lead to the dynamic formation and fission of cooperative groups, accompanied by a dynamic rise and fall of cooperation among agents. The ability of humans to safeguard kin-independent cooperation through gossip and reputation may be, accordingly, closely interlinked with the formation of group-bounded cooperation networks that are under constant reconfiguration, ultimately preventing global and stable cooperation.Social decision makin

Children’s Reporting of Peers’ Behaviour

This thesis describes a mixed-methods investigation of young children’s everyday social communication, focusing on tattling—the reporting of a peer’s negative behaviour to an audience. There are links between tattling and the development of gossip, and thus with the evolution of cooperative norms in humans. Tattling is a daily activity for many children, but has been little studied, especially in preschool contexts. \ud Quantitative sampling and participant observation are used to characterize behavioural reporting among 3- to 4-year-olds in 2 preschools in Belfast, Northern Ireland. Quantitative sampling shows that children in these populations are biased towards reporting negative actions by peers; that they are more likely to report actions of which they themselves are the victims; that they usually tell the truth; that their reports are rarely ignored by staff; and that there are relationships between frequency of tattling and measures of social dominance and relational aggression. Participant observation shows that tattling takes place in a complex social context; that children are generally aware of its effects; and that it is driven by a range of motivations, both self-oriented and group-oriented. \ud Two story recall experiments are described, aimed at testing the hypothesis that negative bias in children’s reports arises from the greater salience of negative behaviour. The experiments do not support this hypothesis, further strengthening the idea that children are acting out of strategic considerations when they report peers’ transgressions. Behavioural reporting in preschool contexts is compared with a sample of transcripts of children’s discourse recorded in 1970s England and stored in the CHILDES database. Examples of tattling and gossip are also found in the eHRAF ethnographic database. The thesis concludes with an interactionist model of the development of tattling and gossip, in which third-party mediation helps to integrate the affective and normative components of children’s developing moral systems.\u