Numerical cognition in bees and other insects

The ability to perceive the number of objects has been known to exist in vertebrates for a few decades, but recent behavioral investigations have demonstrated that several invertebrate species can also be placed on the continuum of numerical abilities shared with birds, mammals, and reptiles. In this review article, we present the main experimental studies that have examined the ability of insects to use numerical information. These studies have made use of a wide range of methodologies, and for this reason it is striking that a common finding is the inability of the tested animals to discriminate numerical quantities greater than four. Furthermore, the finding that bees can not only transfer learnt numerical discrimination to novel objects, but also to novel numerosities, is strongly suggestive of a true, albeit limited, ability to count. Later in the review, we evaluate the available evidence to narrow down the possible mechanisms that the animals might be using to solve the number-based experimental tasks presented to them. We conclude by suggesting avenues of further research that take into account variables such as the animals' age and experience, as well as complementary cognitive systems such as attention and the time sense.This publication was funded by the German Research Foundation (DFG) and the University of Wuerzburg in the funding program Open Access Publishing. Shaowu Zhang was supported by the ARC-CoE in Vision Science

The use of ideas of Information Theory for studying "language" and intelligence in ants

In this review we integrate results of long term experimental study on ant "language" and intelligence which were fully based on fundamental ideas of Information Theory, such as the Shannon entropy, the Kolmogorov complexity, and the Shannon's equation connecting the length of a message ($l$) and its frequency $(p)$, i.e. $l = - \log p$ for rational communication systems. This approach, new for studying biological communication systems, enabled us to obtain the following important results on ants' communication and intelligence: i) to reveal "distant homing" in ants, that is, their ability to transfer information about remote events; ii) to estimate the rate of information transmission; iii) to reveal that ants are able to grasp regularities and to use them for "compression" of information; iv) to reveal that ants are able to transfer to each other the information about the number of objects; v) to discover that ants can add and subtract small numbers. The obtained results show that Information Theory is not only wonderful mathematical theory, but many its results may be considered as Nature laws

Approximations of Algorithmic and Structural Complexity Validate Cognitive-behavioural Experimental Results

We apply methods for estimating the algorithmic complexity of sequences to behavioural sequences of three landmark studies of animal behavior each of increasing sophistication, including foraging communication by ants, flight patterns of fruit flies, and tactical deception and competition strategies in rodents. In each case, we demonstrate that approximations of Logical Depth and Kolmogorv-Chaitin complexity capture and validate previously reported results, in contrast to other measures such as Shannon Entropy, compression or ad hoc. Our method is practically useful when dealing with short sequences, such as those often encountered in cognitive-behavioural research. Our analysis supports and reveals non-random behavior (LD and K complexity) in flies even in the absence of external stimuli, and confirms the "stochastic" behaviour of transgenic rats when faced that they cannot defeat by counter prediction. The method constitutes a formal approach for testing hypotheses about the mechanisms underlying animal behaviour.Comment: 28 pages, 7 figures and 2 table

Predicting business/ICT alignment with AntMiner+.

In this paper we report on the results of a European survey on business/ICT alignment practices. The goal of this study is to come up with some practical guidelines for managers on how to strive for better alignment of ICT investments with business requirements. Based on Luftman's alignment framework we examine 18 ICT management practices belonging to 6 different competency clusters. We use AntMiner+, a rule induction technique, to create an alignment rule set. The results indicate that B/ICT alignment is a multidimensional goal which can only be obtained through focused investments covering different alignment aspects. The obtained rule set is an interesting mix of both formal engineering and social interaction processes and structures. We discuss the implication of the alignment rules for practitioners.Alignment; Artificial ant systems; Business; Business/ICT alignment; Data; Data mining; Framework; Investment; Investments; Management; Management practices; Managers; Practical guidelines; Processes; Requirements; Rules; Structure; Studies; Systems;

Quantitative cognition in carpenter ants

P.dE. is funded by ‘Institut Universitaire de France (IUF)’.Processing information about quantities allows animals to make optimal decisions during many natural contexts, such as foraging, territorial defense, offspring care, mate choice, and intra-sexual competition. Compared to the wealth of information available in vertebrates, much less is known in invertebrates, even though the processing of quantities is equally relevant for both taxa. Here, we used two separate ecologically relevant tasks (brood pile preference and landmark-guided foraging) to investigate two dimensions of quantitative cognition in carpenter ants: spontaneous quantitative judgments and trained use of sequential landmarks. Individual ants spontaneously discriminated between two piles of dummy cocoons both when the choice involved smaller (1 vs. 2, 3, 4) and larger numerical contrasts (2 vs. 4, 6, 8). Ants used both chemical and visual/tactile cues and their performance was dependent on the numerical ratio. In the second task, ants preferentially searched near the trained landmark (out of five identical ones) despite alterations in its position, suggesting that they used ordinal information about its location when searching for food. In this experiment, ants showed a limit at four since their performance drastically decreased when they were trained to the 5th landmark. We showed that carpenter ants use both relative quantity and relative position to make efficient decisions. Our study contributes to the scant body of knowledge available on quantitative cognition in invertebrate species.PostprintPeer reviewe

Swarm intelligence in fish? The difficulty in demonstrating distributed and self-organised collective intelligence in (some) animal groups

AbstractLarger groups often have a greater ability to solve cognitive tasks compared to smaller ones or lone individuals. This is well established in social insects, navigating flocks of birds, and in groups of prey collectively vigilant for predators. Research in social insects has convincingly shown that improved cognitive performance can arise from self-organised local interactions between individuals that integrates their contributions, often referred to as swarm intelligence. This emergent collective intelligence has gained in popularity and been directly applied to groups of other animals, including fish. Despite being a likely mechanism at least partially explaining group performance in vertebrates, I argue here that other possible explanations are rarely ruled out in empirical studies. Hence, evidence for self-organised collective (or ‘swarm’) intelligence in fish is not as strong as it would first appear. These other explanations, the ‘pool-of-competence’ and the greater cognitive ability of individuals when in larger groups, are also reviewed. Also discussed is why improved group performance in general may be less often observed in animals such as shoaling fish compared to social insects. This review intends to highlight the difficulties in exploring collective intelligence in animal groups, ideally leading to further empirical work to illuminate these issues

Utility Rate Equations of Group Population Dynamics in Biological and Social Systems

We present a novel system of equations to describe the evolution of self-organized structured societies (biological or human) composed of several trait groups. The suggested approach is based on the combination of ideas employed in the theory of biological populations, system theory, and utility theory. The evolution equations are defined as utility rate equations, whose parameters are characterized by the utility of each group with respect to the society as a whole and by the mutual utilities of groups with respect to each other. We analyze in detail the cases of two groups (cooperators and defectors) and of three groups (cooperators, defectors, and regulators) and find that, in a self-organized society, neither defectors nor regulators can overpass the maximal fractions of about 10% each. This is in agreement with the data for bee and ant colonies. The classification of societies by their distance from equilibrium is proposed. We apply the formalism to rank the countries according to the introduced metric quantifying their relative stability, which depends on the cost of defectors and regulators as well as their respective population fractions. We find a remarkable concordance with more standard economic ranking based, for instance, on GDP per capita.Comment: Latex file, 39 pages, 8 figure