Preliminary investigation of flexibility in learning color-reward associations in gibbons (<i>Hylobatidae</i>)

Previous studies in learning set formation have shown that most animal species can learn to learn with subsequent novel presentations being solved in fewer presentations than when they first encounter a task. Gibbons (Hylobatidae) have generally struggled with these tasks and do not show the learning to learn pattern found in other species. This is surprising given their phylogenetic position and level of cortical development. However, there have been conflicting results with some studies demonstrating higher level learning abilities in these small apes. This study attempts to clarify whether gibbons can in fact use knowledge gained during one learning task to facilitate performance on a similar, but novel problem that would be a precursor to development of a learning set. We tested 16 captive gibbons' ability to associate color cues with provisioned food items in two experiments where they experienced a period of learning followed by experimental trials during which they could potentially use knowledge gained in their first learning experience to facilitate solution I subsequent novel tasks. Our results are similar to most previous studies in that there was no evidence of gibbons being able to use previously acquired knowledge to solve a novel task. However, once the learning association was made, the gibbons performed well above chance. We found no differences across color associations, indicating learning was not affected by the particular color / reward association. However, there were variations in learning performance with regard to genera. The hoolock (Hoolock leuconedys) and siamang (Symphalangus syndactylus) learned the fastest and the lar group (Hylobates sp.) learned the slowest. We caution these results could be due to the small sample size and because of the captive environment in which these gibbons were raised. However, it is likely that environmental variability in the native habitats of the subjects tested could facilitate the evolution of flexible learning in some genera. Further comparative study is necessary in order to incorporate realistic cognitive variables into foraging models

Life is an Adventure! An agent-based reconciliation of narrative and scientific worldviews\ud

The scientific worldview is based on laws, which are supposed to be certain, objective, and independent of time and context. The narrative worldview found in literature, myth and religion, is based on stories, which relate the events experienced by a subject in a particular context with an uncertain outcome. This paper argues that the concept of “agent”, supported by the theories of evolution, cybernetics and complex adaptive systems, allows us to reconcile scientific and narrative perspectives. An agent follows a course of action through its environment with the aim of maximizing its fitness. Navigation along that course combines the strategies of regulation, exploitation and exploration, but needs to cope with often-unforeseen diversions. These can be positive (affordances, opportunities), negative (disturbances, dangers) or neutral (surprises). The resulting sequence of encounters and actions can be conceptualized as an adventure. Thus, the agent appears to play the role of the hero in a tale of challenge and mystery that is very similar to the "monomyth", the basic storyline that underlies all myths and fairy tales according to Campbell [1949]. This narrative dynamics is driven forward in particular by the alternation between prospect (the ability to foresee diversions) and mystery (the possibility of achieving an as yet absent prospect), two aspects of the environment that are particularly attractive to agents. This dynamics generalizes the scientific notion of a deterministic trajectory by introducing a variable “horizon of knowability”: the agent is never fully certain of its further course, but can anticipate depending on its degree of prospect

Trivial movements and redistribution of polyphagous insect herbivores in heterogeneous vegetation

The aim of this thesis was to study the interplay between movement patterns of polyphagous insect herbivores and vegetation heterogeneity within agricultural fields. I examined if and how 1) host plant species, 2) host plant quality, 3) vegetation architecture, and 4) trap crop physical design influence movement patterns of individuals and spatial distribution of populations. Foragers may aggregate in profitable areas by tactic movement, or by area-restricted search, i.e. by moving randomly but slowing down movement and increasing rate of turning after encountering a profitable patch. Movement patterns of polyphagous herbivores have a high potential for influencing their distribution among hosts differing in quality. However, information on the role random vs. non-random components in their movement behavior is scarce. The results of this thesis show that both host plant species and within species differences in host plant quality affect movement behavior of a polyphagous herbivore, the European tarnished plant bug nymphs. The host plant induced movement patterns also explained the distribution of nymphs in heterogeneous vegetation. Because redistribution was very fast, it appears that no tactic behavior is needed for the nymphs to locate preferred hosts in heterogeneous vegetation composed of small patches. Instead the nymphs may successfully locate superior hosts merely by random movement coupled with sensitivity to local host quality. The physical structure of environment influences redistribution of populations at several spatial scales. At small scale the architecture of vegetation may influence redistribution of insects that move on the plant surface. At large scale e.g. trap crop physical design may affect redistribution of pests. In this thesis I derive a model for predicting the impact of vegetation architecture on the rate of displacement by insects moving on the plant surface. I also present and explore models of the interplay between pest movement and trap crop physical design. The trap crop models suggest that considerable reduction in pest density may be achieved using small trap crop cover with trap crops that the pest distinctly prefers over the crop. It supports also the idea that trap crop placement may have a dramatic impact on the efficiency of the trap crops

Are Individuals Fickle-Minded?

Game theory has been used to model large-scale social events — such as constitutional law, democratic stability, standard setting, gender roles, social movements, communication, markets, the selection of officials by means of elections, coalition formation, resource allocation, distribution of goods, and war — as the aggregate result of individual choices in interdependent decision-making. Game theory in this way assumes methodological individualism. The widespread observation that game theory predictions do not in general match observation has led to many attempts to repair game theory by creating behavioral game theory, which adds corrective terms to the game theoretic predictions in the hope of making predictions that better match observations. But for game theory to be useful in making predictions, we must be able to generalize from an individual’s behavior in one situation to that individual’s behavior in very closely similar situations. In other words, behavioral game theory needs individuals to be reasonably consistent in action if the theory is to have predictive power. We argue on the basis of experimental evidence that the assumption of such consistency is unwarranted. More realistic models of individual agents must be developed that acknowledge the variance in behavior for a given individual

Attentive monitoring of multiple video streams driven by a Bayesian foraging strategy

In this paper we shall consider the problem of deploying attention to subsets of the video streams for collating the most relevant data and information of interest related to a given task. We formalize this monitoring problem as a foraging problem. We propose a probabilistic framework to model observer's attentive behavior as the behavior of a forager. The forager, moment to moment, focuses its attention on the most informative stream/camera, detects interesting objects or activities, or switches to a more profitable stream. The approach proposed here is suitable to be exploited for multi-stream video summarization. Meanwhile, it can serve as a preliminary step for more sophisticated video surveillance, e.g. activity and behavior analysis. Experimental results achieved on the UCR Videoweb Activities Dataset, a publicly available dataset, are presented to illustrate the utility of the proposed technique.Comment: Accepted to IEEE Transactions on Image Processin

Statistical interaction modeling of bovine herd behaviors

While there has been interest in modeling the group behavior of herds or flocks, much of this work has focused on simulating their collective spatial motion patterns which have not accounted for individuality in the herd and instead assume a homogenized role for all members or sub-groups of the herd. Animal behavior experts have noted that domestic animals exhibit behaviors that are indicative of social hierarchy: leader/follower type behaviors are present as well as dominance and subordination, aggression and rank order, and specific social affiliations may also exist. Both wild and domestic cattle are social species, and group behaviors are likely to be influenced by the expression of specific social interactions. In this paper, Global Positioning System coordinate fixes gathered from a herd of beef cows tracked in open fields over several days at a time are utilized to learn a model that focuses on the interactions within the herd as well as its overall movement. Using these data in this way explores the validity of existing group behavior models against actual herding behaviors. Domain knowledge, location geography and human observations, are utilized to explain the causes of these deviations from this idealized behavior

COORDINATION OF LEADER-FOLLOWER MULTI-AGENT SYSTEM WITH TIME-VARYING OBJECTIVE FUNCTION

This thesis aims to introduce a new framework for the distributed control of multi-agent systems with adjustable swarm control objectives. Our goal is twofold: 1) to provide an overview to how time-varying objectives in the control of autonomous systems may be applied to the distributed control of multi-agent systems with variable autonomy level, and 2) to introduce a framework to incorporate the proposed concept to fundamental swarm behaviors such as aggregation and leader tracking. Leader-follower multi-agent systems are considered in this study, and a general form of time-dependent artificial potential function is proposed to describe the varying objectives of the system in the case of complete information exchange. Using Lyapunov methods, the stability and boundedness of the agents\u27 trajectories under single order and higher order dynamics are analyzed. Illustrative numerical simulations are presented to demonstrate the validity of our results. Then, we extend these results for multi-agent systems with limited information exchange and switching communication topology. The first steps of the realization of an experimental framework have been made with the ultimate goal of verifying the simulation results in practice