How do ensembles occupy space?

To find an answer to the title question, an attractiveness function between agents and locations is introduced yielding a phenomenological but generic model for the search for optimal distributions of agents over space. Agents can be seen as, e.g., members of biological populations like colonies of bacteria, swarms, and so on. The global attractiveness between agents and locations is maximized causing (self-propelled) `motion' of agents and, eventually, distinct distributions of agents over space. At the same token spontaneous changes or `decisions' are realized via competitions between agents as well as between locations. Hence, the model's solutions can be considered a sequence of decisions of agents during their search for a proper location. Depending on initial conditions both optimal as well as suboptimal configurations can be reached. For the latter early decision-making are important for avoiding possible conflicts: if the proper moment is missed, then only a few agents can find an optimal solution. Indeed, there is a delicate interplay between the values of the attractiveness function and the constraints as can be expressed by distinct terms of a potential function containing different Lagrange parameters. The model should be viewed as a top-down approach as it describes the dynamics of order parameters, i.e. macroscopic variables that reflect affiliations between agents and locations. The dynamics, however, is modified via so-called cost functions that are interpreted in terms of affinity levels. This interpretation can be seen as an original step towards an understanding of the dynamics at the underlying microscopic level. When focusing on the agent, one may say that the dynamics of an order parameter shows the evolution of an agent's intrinsic `map' for solving the problem of space occupation. Importantly, the dynamics does not necessarily distinguish between evolving (or moving) agents and evolving (or moving) locations though agents are more likely to be actors than the locations. Put differently, an order parameter describes an internal map which is linked to the expectation of an agent to find a certain location. Owing to the dynamical representation, we can therefore follow up the change of these maps over time leading from uncertainty to certainty.     

Emergence of trend trading and its effects in minority game

In this paper, we extended Minority Game (MG) by equipping agents with both value and trend strategies. In the new model, agents (we call them strong-adaptation agents) can autonomically select to act as trend trader or value trader when they game and learn in system. So the new model not only can reproduce stylized factors but also has the potential to investigate into the process of some problems of securities market. We investigated the dynamics of trend trading and its impacts on securities market based on the new model. Our research found that trend trading is inevitable when strong-adaptation agents make decisions by inductive reasoning. Trend trading (of strong-adaptation agents) is not irrational behavior but shows agent's strong-adaptation intelligence, because strong-adaptation agents can take advantage of the pure value agents when they game together in hybrid system. We also found that strong-adaptation agents do better in real environment. The results of our research are different with those of behavior finance researches.     

A Locust-Inspired Model of Collective Marching on Rings

We study the collective motion of autonomous mobile agents in a ringlike environment. The agents’ dynamics are inspired by known laboratory experiments on the dynamics of locust swarms. In these experiments, locusts placed at arbitrary locations and initial orientations on a ring-shaped arena are observed to eventually all march in the same direction. In this work we ask whether, and how fast, a similar phenomenon occurs in a stochastic swarm of simple locust-inspired agents. The agents are randomly initiated as marching either clockwise or counterclockwise on a discretized, wide ring-shaped region, which we subdivide into k concentric tracks of length n. Collisions cause agents to change their direction of motion. To avoid this, agents may decide to switch tracks to merge with platoons of agents marching in their direction. We prove that such agents must eventually converge to a local consensus about their direction of motion, meaning that all agents on each narrow track must eventually march in the same direction. We give asymptotic bounds for the expected time it takes for such convergence or “stabilization” to occur, which depends on the number of agents, the length of the tracks, and the number of tracks. We show that when agents also have a small probability of “erratic”, random track-jumping behavior, a global consensus on the direction of motion across all tracks will eventually be reached. Finally, we verify our theoretical findings in numerical simulations.     

Electronic properties of novel bismuthene nanosheets with adsorption studies of G-series nerve agent molecules – a DFT outlook

In order to confirm the ability of bismuthene nanosheet in detecting the G-series nerve agents, electronic and adsorption properties are investigated. The alteration in the band gap is observed (from the energy band structure) upon adsorption of G-series nerve agents, which results in the modification in the conductivity of BiNS. In addition, to establish the potential application of BiNS as a nerve agent sensor, the adsorption energy, average energy gap variation and Bader charge transfer (vital adsorption properties) are evaluated for the nerve agents, which is physisorbed on BiNS. Furthermore, the supreme statement made in the existing research on adsorption of G-series nerve agents on BiNS is also claimed by comparing the electron density of isolated and nerve agents adsorbed BiNS.     

Network evolution based on minority game with herding behavior

The minority game (MG) is used as a source of information to design complex networks where the nodes represent the playing agents. Differently from classical MG consisting of independent agents, the current model rules that connections between nodes are dynamically inserted or removed from the network according to the most recent game outputs. This way, preferential attachment based on the concept of social distance is controlled by the agents wealth. The time evolution of the network topology, quantitatively measured by usual parameters, is characterized by a transient phase followed by a steady state, where the network properties remain constant. Changes in the local landscapes around individual nodes depend on the parameters used to control network links. If agents are allowed to access the strategies of their network neighbors, a feedback effect on the network structure and game outputs is observed. Such effect, known as herding behavior, considerably changes the dependence of volatility σ on memory size: it is shown that the absolute value of σ as well as the corresponding value of memory size depend both on the network topology and on the way along which the agents make their playing decisions in each game round.     

Social learning with bounded confidence and heterogeneous agents

This paper investigates an opinion formation model in social networks with bounded confidence and heterogeneous agents. The network topologies are shaped by the homophily of beliefs, which means any pair of agents are neighbors only if their belief difference is not larger than a positive constant called the bound of confidence. We consider a model with both informed agents and uninformed agents, the essential difference between which is the informed agents have access to outside signals which are function of the underlying true state of the social event concerned. More precisely, the informed agents update their beliefs by combining the Bayesian posterior beliefs based on their private observations and weighted averages of the beliefs of their neighbors. The uninformed agents update their beliefs simply by linearly combining the beliefs of their neighbors. We find that the whole group can learn the true state only if the bound of confidence is larger than a positive threshold which is related to the population density. Furthermore, simulations show that the proportion of informed agents required for collective learning decreases as the population density increases. By tuning the learning speed of informed agents, we find the following: the higher the speed, the shorter the time needed for the whole group to achieve a steady state, and on the other hand, the higher the speed, the lower the proportion of agents with successful learning — there is a trade-off.     

Consensus pursuit of heterogeneous multi-agent systems under a directed acyclic graph

This paper is concerned with the cooperative target pursuit problem by multiple agents based on directed acyclic graph. The target appears at a random location and moves only when sensed by the agents,and agents will pursue the target once they detect its existence. Since the ability of each agent may be different,we consider the heterogeneous multi-agent systems. According to the topology of the multi-agent systems,a novel consensus-based control law is proposed,where the target and agents are modeled as a leader and followers,respectively. Based on Mason’s rule and signal flow graph analysis,the convergence conditions are provided to show that the agents can catch the target in a finite time. Finally,simulation studies are provided to verify the effectiveness of the proposed approach.     

Synchronization of mobile chaotic agents on connected networks

This work studies the synchronization of a number of mobile agents on a substrate network. Each agent carries a chaotic map and randomly walks on a connected network. The collection of agents consists of another time-varying network derived from the substrate network. It is found that the synchronization conditions of this agent network depend on the average degree of the substrate network’s connectivity, the coupling strength between interacting agents, and the agent density in the network. Synchronization of the agent network on scale-free and ER networks is considered here, and it is found that the scale-free topology is more applicable to synchronize mobile chaotic agents. To get analytical insights, the star graph is taken and considered as a substrate network.     

Explosive synchronization through dynamical environment

We report the emergence of an explosive synchronization transition in the identical oscillators interacting indirectly through a network of dynamical agents. The transition from incoherent state to coherent state and vice–versa in these coupled oscillator exhibits an abrupt as well as irreversible. Such transition depends on the network topology as well as the interaction between the oscillators and dynamical agents rather than degree-frequency correlation in the network of oscillators. The occurrence of explosive synchronization is studied in details by using an appropriate order parameter for limit-cycle oscillators with respect to the different parameters like rewiring probability, average degree, and diffusion rate in dynamical agents.     

Other-regarding preference and the evolutionary prisoner’s dilemma on complex networks

Prevailing models of the evolutionary prisoner’s game on networks always assume that agents are pursuing their own profit maximization. But the results from experimental games show that many agents have other-regarding preference. In this paper, we study the emergence of cooperation from the prisoner’s dilemma game on complex networks while some agents exhibit other-regarding preference such as inequality aversion, envious and guilty emotions. Contrary to common ideas, the simulation results show that the existence of inequality aversion agents does not promote cooperation emergence on a BA (Barabási and Albert) scale-free network in most situations. If the defection attraction is big and agents exhibit strong preference for inequality aversion, the frequency of cooperators will be lower than in situations where no inequality aversion agents exist. In some cases, the existence of the inequality agents will even induce the frequency of cooperators to zero, a feature which is not observed in previous research on the prisoner’s dilemma game when the underlying interaction topology is a BA scale-free network. This means that if an agent cares about equality too much, it will be difficult for cooperation to emerge and the frequency of cooperators will be low on BA networks. The research on the effect of envy or guilty emotions on the emergence of cooperation in the prisoner’s dilemma game on BA networks obtains similar results, though some differences exist. However, simulation results on a WS (Watts and Strogatz) small-world network display another scenario. If agents care about the inequality of agents very much, the WS network favors cooperation emergence in the prisoners’ dilemma game when other-regarding agents exist. If the agent weight on other-regarding is lowered, the cooperation frequencies emerging on a WS network are not much different from those in situations without other-regarding agents, although the frequency of cooperators is lower than those of the situation without other-regarding preference agents sometimes. All the simulation results imply that inequality aversion and its variations can have important effects on cooperation emergence in the prisoner’s dilemma game, and different network topologies have different effects on cooperation emergence in the prisoner’s dilemma game played on complex networks.     

改善三水醋酸钠固液相变性能的实验研究

三水醋酸钠在凝固过程中存在严重的过冷和相分层。用明胶做其防相分层剂,添加不同的成核剂,来解决其过冷问题。最终找到几种能显著改进三水醋酸钠相变特性的添加剂配方,并发现被加入添加剂的三水醋酸钠混合物被加热到的温度对其过冷度有直接影响,同时从晶体结构方面对有效添加剂的选择原则进行了探讨。     

An Evolution Based on Various Energy Strategies

The simplest model of the evolution of agents with different energy strategies is considered. The model is based on the most general thermodynamic ideas and includes the procedures for selection, inheritance, and variability. The problem of finding a universal strategy (principle) as a selection of possible competing strategies is solved. It is shown that when there is non-equilibrium between the medium and agents, a direction in the evolution of agents arises, but at the same time, depending on the conditions of the evolution, different strategies can be successful. However, for this case, the simulation results reveal that in the presence of significant competition of agents, the strategy that has the maximum total energy dissipation of agents arising as a result of evolution turns out to be successful. Thus, it is not the specific strategy that is universal, but the maximization of dissipation. This result discovers an interesting connection between the basic principles of Darwin–Wallace evolution and the maximum entropy production principle.     

Learning, competition and cooperation in simple games

The minority model was introduced to study the competition between agents with limited information. It has the remarkable feature that, as the number of strategies available to the agents increases, the collective gain made by the agents is reduced. This crowd effect arises from the fact that only a minority can profit at each moment, while all agents make their choices using the same input. We show that the properties of the model change drastically if the agents make choices based on their individual stories, keeping all remaining rules unaltered. This variation reduces the intrinsic frustration of the model, and improves the tendency towards cooperation and self organization. We finally study the stable mixing of individual and collective behavior. Received 30 June 1999 and Received in final form 27 September 1999     

Heterogeneous attachment strategies optimize the topology of dynamic wireless networks

In optimizing the topology of wireless networks built of a dynamic set of spatially embedded agents, there are many trade-offs to be dealt with. The network should preferably be as small (in the sense that the average, or maximal, pathlength is short) as possible, it should be robust to failures, not consume too much power, and so on. In this paper, we investigate simple models of how agents can choose their neighbors in such an environment. In our model of attachment, we can tune from one situation where agents prefer to attach to others in closest proximity, to a situation where agents attach to random others regardless of distance (which thus are, on average, further away than the connections to the spatial neighbors). We evaluate this scenario with several performance measures and find that the optimal topologies, for most of the quantities, is obtained for strategies resulting in a mix of most local and a few random connections.     

Effect of organosilane agents on the vulcanizate structure and physical properties of silica-filled solution styrene butadiene rubber compounds

Physical properties of rubber compounds are affected by the filler-rubber interaction, filler dispersion in the rubber matrix, and crosslink structure formed during vulcanization. Organosilane agents are essentially used in silica-rubber compounds to inhibit the formation of silica agglomerates and increase the formation of silica-rubber networks. Generally, organosilane agents have an alkoxysilyl alkyl sulfide structure and are classified into silane coupling and covering agents depending upon the presence of sulfur. Coupling agents have a sulfur moiety and serve as a sulfur donor during the vulcanization process, thus increasing the formation of filler-rubber and chemical crosslink networks. On the other hand, covering agents promote the hydrophobation of silica surfaces, decreasing the adsorption loss of vulcanization additives, which increases the formation of chemical crosslink networks. This implies that organosilane agents can affect the vulcanizate structure, which causes a variation in the properties of silica compounds. Therefore, in this study, the effect of coupling (bis(3-triethoxysilylpropyl)disulfide (TESPD) and bis(3-triethoxysilylpropyl)tetrasulfide (TESPT)) agents and a covering (triethoxy(octyl)silane) agent on the vulcanizate structure and properties of silica compounds was investigated and compared. In the comparative study of coupling and covering agents, the influence of sulfur donors on the formation of vulcanizate structures was investigated. In the case of the coupling agents, the effect of sulfur rank on the vulcanizate structure and properties of silica-rubber compounds was quantitatively analyzed through various characterization techniques.     

Statistical mechanics of money: how saving propensity affects its distribution

We consider a simple model of a closed economic system where the total money is conserved and the number of economic agents is fixed. Analogous to statistical systems in equilibrium, money and the average money per economic agent are equivalent to energy and temperature, respectively. We investigate the effect of the saving propensity of the agents on the stationary or equilibrium probability distribution of money. When the agents do not save, the equilibrium money distribution becomes the usual Gibb's distribution, characteristic of non-interacting agents. However with saving, even for individual self-interest, the dynamics becomes cooperative and the resulting asymmetric Gaussian-like stationary distribution acquires global ordering properties. Intriguing singularities are observed in the stationary money distribution in the market, as functions of the marginal saving propensity of the agents. Received 2 May 2000     

Engineered microsphere contrast agents for optical coherence tomography

Contrast agents are utilized in virtually every imaging modality to enhance diagnostic capabilities. We introduce a novel class of optical contrast agent, namely, encapsulating microspheres, that are based not on fluorescence but on scattering nanoparticles within the shell or core. The agents are suitable for reflection- or scattering-based techniques such as optical coherence tomography, light microscopy, and reflectance confocal microscopy. We characterize the optical properties of gold-, melanin-, and carbon-shelled contrast agents and demonstrate enhancement of optical coherence tomography imaging after intravenous injection of such an agent into a mouse.     

Effects of decision-making on the transport costs across complex networks

We analyse the effects of agents’ decisions on the creation of congestion on a centralised network with ring-and-hub topology. We show that there are two classes of agents each displaying a distinct set of behaviours. The dynamics of the system are driven by an interplay between the formation of, and transition between, unique stable states that arise as the network is varied. We show how the flow of objects across the network can be understood in terms of the ordering and allocation of strategies. Our results show that the existence of congestion in a network is a dynamic process that is as much dependent on the agents’ decisions as it is on the structure of the network itself.     

用放射性测量技术识别化学毒剂

简单介绍了非破坏性识别化学毒剂技术 ,研究了中子诱发 γ谱法、热中子氢含量测量和 X射线成像技术等放射性测量技术识别化学毒剂的原理和实际使用中的一些问题.There are three non destructive radiological methods for identitication of warfare agents and TNT. Their principles and problems related were discussed. Portable isotopic neutron spectroscopy is based on the assay of key elemental composition (such as Cl, P, H, As, S, N) in chemical agents by neutron induced prompt gamma ray analysis. Hydrogen concentration measurement by means of using thermal neutron can be exployed to identify chemical warfare agents and TNT...