Final report key contents: main results accomplished by the EU-Funded project IM-CLeVeR - Intrinsically Motivated Cumulative Learning Versatile Robots

This document has the goal of presenting the main scientific and technological achievements of the project IM-CLeVeR. The document is organised as follows: 1. Project executive summary: a brief overview of the project vision, objectives and keywords. 2. Beneficiaries of the project and contacts: list of Teams (partners) of the project, Team Leaders and contacts. 3. Project context and objectives: the vision of the project and its overall objectives 4. Overview of work performed and main results achieved: a one page overview of the main results of the project 5. Overview of main results per partner: a bullet-point list of main results per partners 6. Main achievements in detail, per partner: a throughout explanation of the main results per partner (but including collaboration work), with also reference to the main publications supporting them

Formation and organisation in robot swarms.

A swarm is defined as a large and independent collection of heterogeneous or homogeneous agents operating in a common environment and seemingly acting in a coherent and coordinated manner. Swarm architectures promote decentralisation and self-organisation which often leads to emergent behaviour. The emergent behaviour of the swarm results from the interactions of the swarm with its environment (or fellow agents), but not as a direct result of design. The creation of artificially simulated swarms or practical robot swarms has become an interesting topic of research in the last decade. Even though many studies have been undertaken using a practical approach to swarm construction, there are still many problems need to be addressed. Such problems include the problem of how to control very simple agents to form patterns; the problem of how an attractor will affect flocking behaviour; and the problem of bridging formation of multiple agents in connecting multiple locations. The central goal of this thesis is to develop early novel theories and algorithms to support swarm robots in. pattern formation tasks. To achieve this, appropriate tools for understanding how to model, design and control individual units have to be developed. This thesis consists of three independent pieces of research work that address the problem of pattern formation of robot swarms in both a centralised and a decentralised way.The first research contribution proposes algorithms of line formation and cluster formation in a decentralised way for relatively simple homogenous agents with very little memory, limited sensing capabilities and processing power. This research utilises the Finite State Machine approach.In the second research contribution, by extending Wilensky's (1999) work on flocking, three different movement models are modelled by changing the maximum viewing angle each agent possesses during the course of changing its direction. An object which releases an artificial potential field is then introduced in the centre of the arena and the behaviours of the collective movement model are studied.The third research contribution studies the complex formation of agents in a task that requires a formation of agents between two locations. This novel research proposes the use Of L-Systems that are evolved using genetic algorithms so that more complex pattern formations can be represented and achieved. Agents will need to have the ability to interpret short strings of rules that form the basic DNA of the formation

Where is cognition? Towards an embodied, situated, and distributed interactionist theory of cognitive activity

In recent years researchers from a variety of cognitive science disciplines have begun to challenge some of the core assumptions of the dominant theoretical framework of cognitivism including the representation-computational view of cognition, the sense-model-plan-act understanding of cognitive architecture, and the use of a formal task description strategy for investigating the organisation of internal mental processes. Challenges to these assumptions are illustrated using empirical findings and theoretical arguments from the fields such as situated robotics, dynamical systems approaches to cognition, situated action and distributed cognition research, and sociohistorical studies of cognitive development. Several shared themes are extracted from the findings in these research programmes including: a focus on agent-environment systems as the primary unit of analysis; an attention to agent-environment interaction dynamics; a vision of the cognizer's internal mechanisms as essentially reactive and decentralised in nature; and a tendency for mutual definitions of agent, environment, and activity. It is argued that, taken together, these themes signal the emergence of a new approach to cognition called embodied, situated, and distributed interactionism. This interactionist alternative has many resonances with the dynamical systems approach to cognition. However, this approach does not provide a theory of the implementing substrate sufficient for an interactionist theoretical framework. It is suggested that such a theory can be found in a view of animals as autonomous systems coupled with a portrayal of the nervous system as a regulatory, coordinative, and integrative bodily subsystem. Although a number of recent simulations show connectionism's promise as a computational technique in simulating the role of the nervous system from an interactionist perspective, this embodied connectionist framework does not lend itself to understanding the advanced 'representation hungry' cognition we witness in much human behaviour. It is argued that this problem can be solved by understanding advanced cognition as the re-use of basic perception-action skills and structures that this feat is enabled by a general education within a social symbol-using environment

Adaptation from interactions between metabolism and behaviour: self-sensitive behaviour in protocells

This thesis considers the relationship between adaptive behaviour and metabolism, using theoretical arguments supported by computational models to demonstrate mechanisms of adaptation that are uniquely available to systems based upon the metabolic organisation of self-production. It is argued how, by being sensitive to their metabolic viability, an organism can respond to the quality of its environment with respect to its metabolic well-being. This makes possible simple but powerful ‘self-sensitive’ adaptive behaviours such as “If I am healthy now, keep doing the same as I have been doing – otherwise do something else.” This strategy provides several adaptive benefits, including the ability to respond appropriately to phenomena never previously experienced by the organism nor by any of its ancestors; the ability to integrate different environmental influences to produce an appropriate response; and sensitivity to the organism’s present context and history of experience. Computational models are used to demonstrate these capabilities, as well as the possibility that self-sensitive adaptive behaviour can facilitate the adaptive evolution of populations of self-sensitive organisms through (i) processes similar to the Baldwin effect, (ii) increasing the likelihood of speciation events, and (iii) automatic behavioural adaptation to changes in the organism itself (such as genetic changes). In addition to these theoretical contributions, a computational model of self-sensitive behaviour is presented that recreates chemotaxis patterns observed in bacteria such as Azospirillum brasilense and Campylobacter jejuni. The models also suggest new explanations for previously unexplained asymmetric distributions of bacteria performing aerotaxis. More broadly, the work advocates further research into the relationship between behaviour and the metabolic organisation of self-production, an organisational property shared by all life. It also acts as an example of how abstract models that target theoretical concepts rather than natural phenomena can play a valuable role in the scientific endeavour

Measuring Behavior 2018 Conference Proceedings

These proceedings contain the papers presented at Measuring Behavior 2018, the 11th International Conference on Methods and Techniques in Behavioral Research. The conference was organised by Manchester Metropolitan University, in collaboration with Noldus Information Technology. The conference was held during June 5th – 8th, 2018 in Manchester, UK. Building on the format that has emerged from previous meetings, we hosted a fascinating program about a wide variety of methodological aspects of the behavioral sciences. We had scientific presentations scheduled into seven general oral sessions and fifteen symposia, which covered a topical spread from rodent to human behavior. We had fourteen demonstrations, in which academics and companies demonstrated their latest prototypes. The scientific program also contained three workshops, one tutorial and a number of scientific discussion sessions. We also had scientific tours of our facilities at Manchester Metropolitan Univeristy, and the nearby British Cycling Velodrome. We hope this proceedings caters for many of your interests and we look forward to seeing and hearing more of your contributions