Effects of Anticipation in Individually Motivated Behaviour on Control and Survival in a Multi-Agent Scenario with Resource Constraints

This is an open access article distributed under the Creative Commons Attribution License CC BY 3.0 which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.Self-organization and survival are inextricably bound to an agent’s ability to control and anticipate its environment. Here we assess both skills when multiple agents compete for a scarce resource. Drawing on insights from psychology, microsociology and control theory, we examine how different assumptions about the behaviour of an agent’s peers in the anticipation process affect subjective control and survival strategies. To quantify control and drive behaviour, we use the recently developed information-theoretic quantity of empowerment with the principle of empowerment maximization. In two experiments involving extensive simulations, we show that agents develop risk-seeking, risk-averse and mixed strategies, which correspond to greedy, parsimonious and mixed behaviour. Although the principle of empowerment maximization is highly generic, the emerging strategies are consistent with what one would expect from rational individuals with dedicated utility models. Our results support empowerment maximization as a universal drive for guided self-organization in collective agent systemsPeer reviewedFinal Published versio

An Analysis of Adaptation as a Response to Climate Change

Climate change is likely to have relevant effects on our future socio-economic systems. It is therefore important to identify how markets and policy jointly react to expected climate change to protect our societies and well-being. This study addresses this issue by carrying out an integrated analysis of both optimal mitigation and adaptation at the global and regional level. Adaptation responses are disentangled into three different modes: reactive adaptation, proactive (or anticipatory) adaptation, and investments in innovation for adaptation purposes. The size, the timing, the relative contribution to total climate-related damage reduction, and the benefit-cost ratios of each of these strategies are assessed for the world as a whole, and for developed and developing countries in both a cooperative and a non-cooperative setting. The study also takes into account the role of price signals and markets in inducing and diffusing adaptation. This leads to two scenarios: A pessimistic one, in which policy-driven adaptation bears the burden, together with mitigation, of reducing climate damage; and an optimistic one, in which markets also autonomously contribute to reducing some damages by modifying sectoral structure, international trade flows, capital distribution and land allocation. For all scenarios, the costs and benefits of adaptation are assessed using WITCH, an integrated assessment, intertemporal optimization, forward-looking model. Extensive sensitivity analysis with respect to the size of climate damages and of the discount rate has also been carried out.Climate change impacts, mitigation, adaptation, integrated assessment model

Social Simulation and Analysis of the Dynamics of Criminal Hot Spots

Within the field of Criminology, the spatio-temporal dynamics of crime are an important subject of study. In this area, typical questions are how the behaviour of offenders, targets, and guardians can be explained and predicted, as well as the emergence and displacement of criminal hot spots. In this article we present a combination of software tools that can be used as an experimental environment to address such questions. In particular, these tools comprise an agent-based simulation model, a verification tool, and a visualisation tool. The agent-based simulation model specifically focuses on the interplay between hot spots and reputation. Using this environment, a large number of simulation runs have been performed, of which results have been formally analysed. Based on these results, we argue that the presented environment offers a valuable approach to analyse the dynamics of criminal hot spots.Agent-Based Modelling, Criminal Hot Spots, Displacement, Reputation, Social Simulation, Analysis

Multi-Agent Reinforcement Learning for Adaptive Mesh Refinement

Adaptive mesh refinement (AMR) is necessary for efficient finite element simulations of complex physical phenomenon, as it allocates limited computational budget based on the need for higher or lower resolution, which varies over space and time. We present a novel formulation of AMR as a fully-cooperative Markov game, in which each element is an independent agent who makes refinement and de-refinement choices based on local information. We design a novel deep multi-agent reinforcement learning (MARL) algorithm called Value Decomposition Graph Network (VDGN), which solves the two core challenges that AMR poses for MARL: posthumous credit assignment due to agent creation and deletion, and unstructured observations due to the diversity of mesh geometries. For the first time, we show that MARL enables anticipatory refinement of regions that will encounter complex features at future times, thereby unlocking entirely new regions of the error-cost objective landscape that are inaccessible by traditional methods based on local error estimators. Comprehensive experiments show that VDGN policies significantly outperform error threshold-based policies in global error and cost metrics. We show that learned policies generalize to test problems with physical features, mesh geometries, and longer simulation times that were not seen in training. We also extend VDGN with multi-objective optimization capabilities to find the Pareto front of the tradeoff between cost and error.Comment: 24 pages, 18 figure

Radically enactive high cognition

I advance the Radically Enactive Cognition (REC) program by developing Hutto & Satne’s (2015) and Hutto & Myin’s (2017) idea that contentful cognition emerges through sociocultural activities, which require a contentless form of intentionality. Proponents of REC then face a functional challenge: what is the function of higher cognitive skills, given the empirical findings that engaging in higher-cognitive activities is not correlated with cognitive amelioration (Kornblith, 2012)? I answer that functional challenge by arguing that higher cognition is an adaptive tool of the social systems we are embedded in, therefore, it is not necessarily aimed at achieving better cognitive states. In order to do so, I suggest interpreting key insights from autopoietic enactivism through REC lenses