Social Learning in a Multi-Agent System

In a persistent multi-agent system, it should be possible for new agents to benefit from the accumulated learning of more experienced agents. Parallel reasoning can be applied to the case of newborn animals, and thus the biological literature on social learning may aid in the construction of effective multi-agent systems. Biologists have looked at both the functions of social learning and the mechanisms that enable it. Many researchers have focused on the cognitively complex mechanism of imitation; we will also consider a range of simpler mechanisms that could more easily be implemented in robotic or software agents. Research in artificial life shows that complex global phenomena can arise from simple local rules. Similarly, complex information sharing at the system level may result from quite simple individual learning rules. We demonstrate in simulation that simple mechanisms can outperform imitation in a multi-agent system, and that the effectiveness of any social learning strategy will depend on the agents' environment. Our simple mechanisms have obvious advantages in terms of robustness and design costs

Optimizing combat capabilities by modeling combat as a complex adaptive system

Procuring combat systems in the Department of Defense is a balancing act where many variables, only some under control of the department, shift simultaneously. Technology changes non-linearly, providing new opportunities and new challenges to the existing and potential force. Money available changes year over year to fit into the overall US Government budget. Numbers of employees change through political demands rather than by cost-effectiveness considerations. The intent is to provide the best mix of equipment to field the best force against an expected enemy while maintaining adequate capability against the unexpected. Confounding this desire is the inability of current simulations to dynamically model changing capabilities and the very large universe of potential combinations of equipment and tactics.;The problem can be characterized as a stochastic, mixed-integer, non-linear optimization problem. This dissertation proposes to combine an agent-based model developed to test solutions that constitute both equipment capabilities and tactics with a co-evolutionary genetic algorithm to search this hyper-dimensional solution space. In the process, the dissertation develops the theoretical underpinning for using agent-based simulations to model combat. It also provides the theoretical basis for improvement of search effectiveness by co-evolving multiple systems simultaneously, which increases exploitation of good schemata and widens exploration of new schemata. Further, it demonstrates the effectiveness of using agent-based models and co-evolution in this application confirming the theoretical results.;An open research issue is the value of increased information in a system. This dissertation uses the combination of an agent-based model with a co-evolutionary genetic algorithm to explore the value added by increasing information in a system. The result was an increased number of fit solutions, rather than an increase in the fitness of the best solutions. Formerly unfit solutions were improved by increasing the information available making them competitive with the most fit solutions whereas already fit solutions were not improved

The pre-oviposition behaviour of Pieris rapae L.

This thesis reports the results of investigations on aspects of the pre-oviposition behaviour of Pieris rapae L. (Lepidoptera: Pieridae) in relation to host plant finding and acceptance. Investigations were carried out into various aspects of the influence of sensory cues on host plant finding including the effect of colour and host plant extracts. The results showed that the number of landings was strongly influenced by colour (P<0.001) and that extracts containing contact stimulants also increased the number of landings (P<0.05).Volatile extracts were also tested in a wind tunnel and the results showed that the extracts increased the number and duration of flights as compared to the solvent controls (P<0.05). However, there was no evidence that the volatile extracts tested acted as attractants. Volatile extracts applied to non-host plants increased the proportion of landings as compared to the controls (P<0.05).The role of different sensory cues (volatile extracts, colour contact stimulants), from three host plants with differing acceptabilities were investigated in order to assess the relative importance of each cue. The results showed that the variety tested had a significant influence on the number of landings and eggs laid. Volatile extracts from the three varieties were prepared and their effect on landing in a choice and no-choice test with model plants was carried out. The volatile extracts significantly increased (P<0.05) the number of landings on the treated plants as compared to the controls.The effect of prior experience was also investigated using three host plants with differing acceptabilities to P. rapae. The results showed that the effect of prior experience (P>0.05) itself was not a significant explanatory variable for the number of eggs laid, however, the host plant variety used was a significant explanatory variable (PcO.OOl). Additionally, there was a significant interaction between these two factors (P<0.05). In a separate experiment, more detailed behavioural observations of the females were made of ovipositing females. The results once again showed that the prior experience treatment was not a significant explanatory variable (P>0.05) as was the host plant varieties used (P>0.05). The interaction between these two factors was statistically significant (PcO.OOl) for all of the behaviours considered. However, when the analysis of the data was repeated with the number of landings used as a covariate in the analysis, the interaction between prior experience and host plant variety was found to be non-significant (P>0.05) for all post-alighting behaviours. Therefore, it would appear that the main effect of prior experience on P. rapae is on the choice of landing site and other ovipositional behaviours are not affected.Finally, an artificial life model of the pre-oviposition behaviour of P. rapae is proposed

A complex systems approach to education in Switzerland

The insights gained from the study of complex systems in biological, social, and engineered systems enables us not only to observe and understand, but also to actively design systems which will be capable of successfully coping with complex and dynamically changing situations. The methods and mindset required for this approach have been applied to educational systems with their diverse levels of scale and complexity. Based on the general case made by Yaneer Bar-Yam, this paper applies the complex systems approach to the educational system in Switzerland. It confirms that the complex systems approach is valid. Indeed, many recommendations made for the general case have already been implemented in the Swiss education system. To address existing problems and difficulties, further steps are recommended. This paper contributes to the further establishment complex systems approach by shedding light on an area which concerns us all, which is a frequent topic of discussion and dispute among politicians and the public, where billions of dollars have been spent without achieving the desired results, and where it is difficult to directly derive consequences from actions taken. The analysis of the education system's different levels, their complexity and scale will clarify how such a dynamic system should be approached, and how it can be guided towards the desired performance