Autonomous and non-autonomous traits mediate social cooperation in Dictyostelium discoideum

In the trishanku (triA(-)) mutant of the social amoeba Dictyostelium discoideum, aggregates are smaller than usual and the spore mass is located mid-way up the stalk, not at the apex. We have monitored aggregate territory size, spore allocation and fruiting body morphology in chimaeric groups of (quasi-wild-type) Ax2 and triA(-) cells. Developmental canalisation breaks down in chimaeras and leads to an increase in phenotypic variation. A minority of triA(-) cells causes largely Ax2 aggregation streams to break up; the effect is not due to the counting factor. Most chimaeric fruiting bodies resemble those of Ax2 or triA(-). Others are double-deckers with a single stalk and two spore masses, one each at the terminus and midway along the stalk. The relative number of spores belonging to the two genotypes depends both on the mixing ratio and on the fruiting body morphology. In double-deckers formed from 1:1 chimaeras, the upper spore mass has more Ax2 spores, and the lower spore mass more triA(-) spores, than expected. Thus, the traits under study depend partly on the cells' own genotype and partly on the phenotypes, and so genotypes, of other cells: they are both autonomous and non-autonomous. These findings strengthen the parallels between multicellular development and behaviour in social groups. Besides that, they reinforce the point that a trait can be associated with a genotype only in a specified context.

Self Assessment-Based Decision Making for Multiagent Cooperative Search

This paper addresses a search problem with multiple limited capability search agents in a partially connected dynamical networked environment under different information structures. A self assessment-based decision-making scheme for multiple agents is proposed that uses a modified negotiation scheme with low communication overheads. The scheme has attractive features of fast decision-making and scalability to large number of agents without increasing the complexity of the algorithm. Two models of the self assessment schemes are developed to study the effect of increase in information exchange during decision-making. Some analytical results on the maximum number of self assessment cycles, effect of increasing communication range, completeness of the algorithm, lower bound and upper bound on the search time are also obtained. The performance of the various self assessment schemes in terms of total uncertainty reduction in the search region, using different information structures is studied. It is shown that the communication requirement for self assessment scheme is almost half of the negotiation schemes and its performance is close to the optimal solution. Comparisons with different sequential search schemes are also carried out. Note to Practitioners-In the futuristic military and civilian applications such as search and rescue, surveillance, patrol, oil spill, etc., a swarm of UAVs can be deployed to carry out the mission for information collection. These UAVs have limited sensor and communication ranges. In order to enhance the performance of the mission and to complete the mission quickly, cooperation between UAVs is important. Designing cooperative search strategies for multiple UAVs with these constraints is a difficult task. Apart from this, another requirement in the hostile territory is to minimize communication while making decisions. This adds further complexity to the decision-making algorithms. In this paper, a self-assessment-based decision-making scheme, for multiple UAVs performing a search mission, is proposed. The agents make their decisions based on the information acquired through their sensors and by cooperation with neighbors. The complexity of the decision-making scheme is very low. It can arrive at decisions fast with low communication overheads, while accommodating various information structures used for increasing the fidelity of the uncertainty maps. Theoretical results proving completeness of the algorithm and the lower and upper bounds on the search time are also provided.

Sex and physiological state influence the rate of resource acquisition and monopolisation in urban free-ranging dogs, Canis familiaris

In animal populations, the constraints of energy and time can cause intraspecific variation in foraging behaviour. The proximate developmental mediators of such variation are often the mechanisms underlying perception and associative learning. Here, experience-dependent changes in foraging behaviour and their consequences were investigated in an urban population of free-ranging dogs, Canis familiaris by continually challenging them with the task of food extraction from specially crafted packets. Typically, males and pregnant/lactating (PL) females extracted food using the sophisticated `gap widening' technique, whereas non-pregnant/non-lactating (NPNL) females, the relatively underdeveloped `rip opening' technique. In contrast to most males and PL females (and a few NPNL females) that repeatedly used the gap widening technique and improved their performance in food extraction with experience, most NPNL females (and a few males and PL females) non-preferentially used the two extraction techniques and did not improve over successive trials. Furthermore, the ability of dogs to sophisticatedly extract food was positively related to their ability to improve their performance with experience. Collectively, these findings demonstrate that factors such as sex and physiological state can cause differences among individuals in the likelihood of learning new information and hence, in the rate of resource acquisition and monopolization.