Constrained Interactions and Social Coordination

We consider a co-evolutionary model of social coordination and network formation whereagents may decide on an action in a 2 x 2- coordination game and on whom to establish costly links to. We find that a payoff dominant convention is selected for a wider parameter range when agents may only support a limited number of links as compared to a scenario where agents are not constrained in their linking choice. The main reason behind this result is that constrained interactions create a tradeoff between the interactions an agent has and those he would rather have. Further, we discuss convex linking costs and provide suffcient conditions for the payoff dominant convention to be selected in mxm coordination games.

Constrained Interactions and Social Coordination

We consider a co-evolutionary model of social coordination and network formation where agents may decide on an action in a 2x2 - coordination game and on whom to establish costly links to. We find that a payoff domination convention is selected for a wider parameter range when agents may only support a limited number of links as compared to a scenario where agents are not constrained in their linking choice. The main reason behind this result is that whenever there is a small cluster of agents playing the efficient strategy other players want to link up to those layers and choose the efficient action

Coordinated constraint relaxation using a distributed agent protocol

The interactions among agents in a multi-agent system for coordinating a distributed, problem solving task can be complex, as the distinct sub-problems of the individual agents are interdependent. A distributed protocol provides the necessary framework for specifying these interactions. In a model of interactions where the agents' social norms are expressed as the message passing behaviours associated with roles, the dependencies among agents can be specified as constraints. The constraints are associated with roles to be adopted by agents as dictated by the protocol. These constraints are commonly handled using a conventional constraint solving system that only allows two satisfactory states to be achieved - completely satisfied or failed. Agent interactions then become brittle as the occurrence of an over-constrained state can cause the interaction between agents to break prematurely, even though the interacting agents could, in principle, reach an agreement. Assuming that the agents are capable of relaxing their individual constraints to reach a common goal, the main issue addressed by this thesis is how the agents could communicate and coordinate the constraint relaxation process. The interaction mechanism for this is obtained by reinterpreting a technique borrowed from the constraint satisfaction field, deployed and computed at the protocol level.The foundations of this work are the Lightweight Coordination Calculus (LCC) and the distributed partial Constraint Satisfaction Problem (CSP). LCC is a distributed interaction protocol language, based on process calculus, for specifying and executing agents' social norms in a multi-agent system. Distributed partial CSP is an extension of partial CSP, a means for managing the relaxation of distributed, over-constrained, CSPs. The research presented in this thesis concerns how distributed partial CSP technique, used to address over-constrained problems in the constraint satisfaction field, could be adopted and integrated within the LCC to obtain a more flexible means for constraint handling during agent interactions. The approach is evaluated against a set of overconstrained Multi-agent Agreement Problems (MAPs) with different levels of hardness. Not only does this thesis explore a flexible and novel approach for handling constraints during the interactions of heterogeneous and autonomous agents participating in a problem solving task, but it is also grounded in a practical implementation

Cohesion, team mental models, and collective efficacy: Towards an integrated framework of team dynamics in sport

A nomological network on team dynamics in sports consisting of a multi-framework perspective is introduced and tested. The aim was to explore the interrelationship among cohesion, team mental models (TMM), collective-efficacy (CE), and perceived performance potential (PPP). Three hundred and forty college-aged soccer players representing 17 different teams (8 female and 9 male) participated in the study. They responded to surveys on team cohesion, TMM, CE and PPP. Results are congruent with the theoretical conceptualization of a parsimonious view of team dynamics in sports. Specifically, cohesion was found to be an exogenous variable predicting both TMM and CE beliefs. TMM and CE were correlated and predicted PPP, which in turn accounted for 59% of the variance of objective performance scores as measured by teams’ season record. From a theoretical standpoint, findings resulted in a parsimonious view of team dynamics, which may represent an initial step towards clarifying the epistemological roots and nomological network of various team-level properties. From an applied standpoint, results suggest that team expertise starts with the establishment of team cohesion. Following the establishment of cohesiveness, teammates are able to advance team-related schemas and a collective sense of confidence. Limitations and key directions for future research are outlined

Social-Aware Coordination of Multi-robot Systems Based on Institutions

Institutional robotics (IR) is an approach to the coordination of multi-robot systems that draws inspiration from social sciences, namely from institutional economics. Using the concept of institution, it aims to provide a comprehensive strategy for specifying social interactions (e.g., norms, roles, hierarchies) among robots. In previous work, we have introduced a control methodology for multi-robot systems that takes into account institutions in order to create an Institutional Agent Controller (IAC) that captures such social interactions. In this chapter, the IAC design methodology is validated in a case study concerned with a swarm of 40 real, resource-constrained robots which has to maintain wireless connectivity. We then investigate a second case study dealing with more complex social interactions, showing that institutional roles can effectively help a multi-robot system to coordinate and improve performance in a given task of social nature. Given the fact that institutions are one of the tools in use within human societies to shape social interactions, our intuition is that IR can also facilitate coordination with humans in scenarios involving many-to-many human–robot interactions. We discuss how the IR concepts and the IAC design methodology can be implemented in real-world scenarios where multiple robots must interact with multiple humans in a socially aware manner

A generic model of dyadic social relationships

We introduce a model of dyadic social interactions and establish its correspondence with relational models theory (RMT), a theory of human social relationships. RMT posits four elementary models of relationships governing human interactions, singly or in combination: Communal Sharing, Authority Ranking, Equality Matching, and Market Pricing. To these are added the limiting cases of asocial and null interactions, whereby people do not coordinate with reference to any shared principle. Our model is rooted in the observation that each individual in a dyadic interaction can do either the same thing as the other individual, a different thing or nothing at all. To represent these three possibilities, we consider two individuals that can each act in one out of three ways toward the other: perform a social action X or Y, or alternatively do nothing. We demonstrate that the relationships generated by this model aggregate into six exhaustive and disjoint categories. We propose that four of these categories match the four relational models, while the remaining two correspond to the asocial and null interactions defined in RMT. We generalize our results to the presence of N social actions. We infer that the four relational models form an exhaustive set of all possible dyadic relationships based on social coordination. Hence, we contribute to RMT by offering an answer to the question of why there could exist just four relational models. In addition, we discuss how to use our representation to analyze data sets of dyadic social interactions, and how social actions may be valued and matched by the agents

"Open Innovation" and "Triple Helix" Models of Innovation: Can Synergy in Innovation Systems Be Measured?

The model of "Open Innovations" (OI) can be compared with the "Triple Helix of University-Industry-Government Relations" (TH) as attempts to find surplus value in bringing industrial innovation closer to public R&D. Whereas the firm is central in the model of OI, the TH adds multi-centeredness: in addition to firms, universities and (e.g., regional) governments can take leading roles in innovation eco-systems. In addition to the (transversal) technology transfer at each moment of time, one can focus on the dynamics in the feedback loops. Under specifiable conditions, feedback loops can be turned into feedforward ones that drive innovation eco-systems towards self-organization and the auto-catalytic generation of new options. The generation of options can be more important than historical realizations ("best practices") for the longer-term viability of knowledge-based innovation systems. A system without sufficient options, for example, is locked-in. The generation of redundancy -- the Triple Helix indicator -- can be used as a measure of unrealized but technologically feasible options given a historical configuration. Different coordination mechanisms (markets, policies, knowledge) provide different perspectives on the same information and thus generate redundancy. Increased redundancy not only stimulates innovation in an eco-system by reducing the prevailing uncertainty; it also enhances the synergy in and innovativeness of an innovation system.Comment: Journal of Open Innovations: Technology, Market and Complexity, 2(1) (2016) 1-12; doi:10.1186/s40852-016-0039-

Product market reforms, labour market institutions and unemployment

We analyze the impact of product market competition on unemployment and wages, and how this depends on labour market institutions. We use differential changes in regulations across OECD countries over the 1980s and 1990s to identify the effects of competition. We find that increased product market competition reduces unemployment, and that it does so more in countries with labour market institutions that increase worker bargaining power. The theoretical intuition is that both firms with market power and unions with bargaining power are constrained in their behaviour by the elasticity of demand in the product market. We also find that the effect of increased competition on real wages is beneficial to workers, but less so when they have high bargaining power. Intuitively, real wages increase through a drop in the general price level, but workers with bargaining power lose out somewhat from a reduction in the rents that they had previously captured