The benefit of being physically present: A survey of experimental works comparing copresent robots,telepresent robots and virtual agents

The effects of physical embodiment and physical presence were explored through a survey of 33 experimental works comparing how people interacted with physical robots and virtual agents. A qualitative assessment of the direction of quantitative effects demonstrated that robots were more persuasive and perceived more positively when physically present in a user׳s environment than when digitally-displayed on a screen either as a video feed of the same robot or as a virtual character analog; robots also led to better user performance when they were collocated as opposed to shown via video on a screen. However, participants did not respond differently to physical robots and virtual agents when both were displayed digitally on a screen – suggesting that physical presence, rather than physical embodiment, characterizes people׳s responses to social robots. Implications for understanding psychological response to physical and virtual agents and for methodological design are discussed.     

MANAGING RESPONSIVE ENVIRONMENTS WITH SOFTWARE AGENTS

Responsive environments are physical surroundings whose components change their behavior to accommodate the presence of people as well as other components. We describe a means to manage responsive environments whereby each component is dynamically assigned a software agent. Software agents are autonomous and reactive/proactive programs that communicate via message-passing. Arbitrary functionalities can be encoded in such agents, reflecting the capabilities of the components they represent, as well as extending them. Ours is a flexible and scalable approach allowing the gradual population of environments with physical devices and their agents.     

Velocity-based modeling of physical interactions in dense crowds

We present an interactive algorithm to model physics-based interactions in dense crowds. Our approach is capable of modeling both physical forces and interactions between agents and obstacles, while also allowing the agents to anticipate and avoid upcoming collisions during local navigation. We combine velocity-based collision-avoidance algorithms with external physical forces. The overall formulation produces various effects of forces acting on agents and crowds, including balance recovery motion and force propagation through the crowd. We further extend our method to model more complex behaviors involving social and cultural rules. We use finite-state machines to specify a series of behaviors and demonstrate our approach on many complex scenarios. Our algorithm can simulate a few thousand agents at interactive rates and can generate many emergent behaviors.     

Combined strength of holons,agents and function blocks in cyber-physical systems

This paper presents a novel approach to implementing cyber-physical systems (CPS) using the combined strength of holons, agents and function blocks. Within the context, a CPS is represented by a holarchy of multiple holons. Each holon possesses a logical part and a physical part, which mimic the cyber and physical entities of the CPS. During implementation, the two parts of a holon are realised by agents and function blocks for information processing and materials processing, respectively. The objective of this research is to provide a concept map and associate a CPS with holons, agents and function blocks for the ease of system implementation in decentralised or cloud environment.     

Engineering framework for agent-based manufacturing control

MAS (multi-agent systems) and HMS (holonic manufacturing systems) are enabling the vision of the Plug & Play Factory and paving the way for future autonomous production systems. This paper reviews the state of the art in implementations of agent-based manufacturing systems, and identifies the lack of engineering tools as a technological gap for widespread industrial adoption of the paradigm. The lack of tools limits the implementation of agent-based manufacturing systems within reach of only a handful of domain experts. One of the current challenges for the design and implementation of intelligent agents is the simulation and visualization of the agent societies. This issue is significant as soon as the software agent is embedded into a mechatronic device or machine resulting in a physical intelligent agent with 3D-mechanical restrictions. These mechanical restrictions must be considered in the negotiations between agents in order to coordinate the execution of physical operations. This paper presents an engineering framework that contributes towards overcoming the identified technology gap. The framework consists of a comprehensive set of software tools that facilitate the creation, simulation and visualization of agent societies. The 3D framework is innovative in fully emulating the deployed agents, recreating multi-agent negotiations and societies that coordinate and execute control of assembly operations. The documented research describes the methodology for the 3D representation of individual physical agents, the related identified objects present in the interaction protocols, and the assembly features and clustering algorithms.     

Stability and oscillations in single-species processes with past memory†

In this work, by employing very elementary mathematical analysis, sufficient conditions for oscillations, non-oscillations and stability of single-species hereditary processes in biological, medical, physical and social sciences are given. The obtained conditions are expressed in terms of rate functions and time-delays. Moreover, they are algebraically simple and easy to compute. It is shown that certain classes of time-delays are both stabilizing and oscillizing agents, and that some other classes of delays are only stabilizing agents. Finally, the usefulness of the oscillatory and stability analysis of single-species processes has been demonstrated by exhibiting several well known examples of single-species processes in biological, medical, physical and social sciences in a coherent way.     

Quantum Physical Symbol Systems

Because intelligent agents employ physically embodied cognitive systems to reason about the world, their cognitive abilities are constrained by the laws of physics. Scientists have used digital computers to develop and validate theories of physically embodied cognition. Computational theories of intelligence have advanced our understanding of the nature of intelligence and have yielded practically useful systems exhibiting some degree of intelligence. However, the view of cognition as algorithms running on digital computers rests on implicit assumptions about the physical world that are incorrect. Recently, the view is emerging of computing systems as goal-directed agents, evolving during problem solving toward improved world models and better task performance. A full realization of this vision requires a new logic for computing that incorporates learning from experience as an intrinsic part of the logic, and that permits full exploitation of the quantum nature of the physical world. This paper proposes a theory of physically embodied cognitive agents founded upon first-order logic, Bayesian decision theory, and quantum physics. An abstract architecture for a physically embodied cognitive agent is presented. The cognitive aspect is represented as a Bayesian decision theoretic agent; the physical aspect is represented as a quantum process; and these aspects are related through von Neumann’s principle of psycho-physical parallelism. Alternative metaphysical positions regarding the meaning of quantum probabilities and the role of efficacious choices by agents are discussed in relation to the abstract agent architecture. The concepts are illustrated with an extended example from the domain of science fiction.     

WSN in cyber physical systems: Enhanced energy management routing approach using software agents

Recently, the cyber physical system has emerged as a promising direction to enrich the interactions between physical and virtual worlds. Meanwhile, a lot of research is dedicated to wireless sensor networks as an integral part of cyber physical systems. A wireless sensor network (WSN) is a wireless network consisting of spatially distributed autonomous devices that use sensors to monitor physical or environmental conditions. These autonomous devices, or nodes, combine with routers and a gateway to create a typical WSN system. Shrinking size and increasing deployment density of wireless sensor nodes implies the smaller equipped battery size. This means emerging wireless sensor nodes must compete for efficient energy utilization to increase the WSN lifetime. The network lifetime is defined as the time duration until the first sensor node in a network fails due to battery depletion. One solution for enhancing the lifetime of WSN is to utilize mobile agents. In this paper, we propose an agent-based approach that performs data processing and data aggregation decisions locally i.e., at nodes rather than bringing data back to a central processor (sink). Our proposed approach increases the network lifetime by generating an optimal routing path for mobile agents to transverse the network. The proposed approach consists of two phases. In the first phase, Dijkstra’s algorithm is used to generate a complete graph to connect all source nodes in a WSN. In the second phase, a genetic algorithm is used to generate the best-approximated route for mobile agents in a radio harsh environment to route the sensory data to the base-station. To demonstrate the feasibility of our approach, a formal analysis and experimental results are presented.     

SAW-PECH传感器对有机硫类毒剂吸附行为的研究

研究了以聚环氧氯丙烷(Poly(epichlorohydrin),PECH)为敏感膜的声表面波(surface acoustic wave,SAW)双通道延迟线传感器对有机硫类毒剂吸附行为的特性.实验表明该传感器的灵敏性符合Arrhenius方程负的温度依赖性,PECH敏感膜对有机硫类毒剂是物理吸附;以理想气体多分子吸附BET理论为模型,对该敏感膜检测有机硫类毒剂的吸附机理进行了讨论,并计算出△E及PECH敏感膜的比表面积.     

Exploiting Spatial Locality and Heterogeneity of Agents for Search and Rescue Teamwork*

We propose coordination mechanisms for multiple heterogeneous physical agents that operate in city‐scale disaster scenarios, where they need to find and rescue people and extinguish fires. Large‐scale disasters are characterized by limited and unreliable communications; dangerous events that may disable agents; uncertainty about the location, duration, and type of tasks; and stringent temporal constraints on task completion times. In our approach, agents form teams with other agents that are in the same geographical area. Our algorithms either yield stable teams formed up front and never change, fluid teams where agents can change teams as need arises, or teams that restrict the types of agents that can belong to the same team. We compare our teaming algorithms against a baseline algorithm in which agents operate independently of others and two state‐of‐the‐art coordination mechanisms. Our algorithms are tested in city‐scale disaster simulations using the RoboCup Rescue simulator. Our experiments with different city maps show that, in general, forming teams leads to increased task completion and, specifically, that our teaming method that restricts the types of agents in a team outperforms the other methods.     

Tropism-based cognition: a novel software architecture for agents in colonies

A novel architecture for agents in colonies has been developed in order to investigate certain forms of group interaction. Specifically, we are interested in the extent to which overall goals for a colony can be achieved when each agent is only aware of limited local goals, whether the architecture allows for emergence of unexpected behaviour, and whether explicit communication among agents facilitates or hinders task performance. The architecture supports several forms of learning. Large colonies of agents (as many as 100) have been studied in simulation experiments, where they carried out fetch-and-carry tasks in the presence of predators and with limited energy reserves. In addition, a physical colony of four agents has been fabricated with the same architecture, to ensure that the behaviours observed in simulation were also present in the hardware implementations.     

An efficient scheme for multi-party quantum state sharing of an arbitrary multi-qubit state with one GHZ channel

We present an innovative and extremely efficient scheme to share an arbitrary multi-qubit state between n agents with only 1 GHZ channel under control of m agents in a network. Compared with existing ones in this literature, our scheme requires less communication resources, least qubits and only three physical favorable simple operations (single-qubit measurement, Bell-basis measurement and CNOT gate operations) are included, leading to a higher overall efficiency.     

Adaptive agent abstractions to speed up spatial agent-based simulations

Simulating fine-grained agent-based models requires extensive computational resources. In this article, we present an approach that reduces the number of agents by adaptively abstracting groups of spatial agents into meta-agents that subsume individual behaviours and physical forms. Particularly, groups of agents that have been clustering together for a sufficiently long period of time are detected by observer agents and then abstracted into a single meta-agent. Observers periodically test meta-agents to ensure their validity, as the dynamics of the simulation may change to a point where the individual agents do not form a cluster any more. An invalid meta-agent is removed from the simulation and subsequently, its subsumed individual agents will be put back in the simulation. The same mechanism can be applied on meta-agents thus creating adaptive abstraction hierarchies during the course of a simulation. Experimental results on the simulation of the blood coagulation process show that the proposed abstraction mechanism results in the same system behaviour while speeding up the simulation.     

Using finite state automata to produce self-optimization andself-control

A simple game provides a framework within which agents can spontaneously self-organize. In this paper, we present this game, and develop basic theory underlying a robust method for distributed coordination based on this game. This method makes use of finite state automata-one associated with each agent-which guide the agents. We give a new, general method of analysis of these systems, which previously had been studied only in limited cases. We also provide a physical example, which should hint at the type of problems resolvable using this method     

MULTI-AGENT INFRASTRUCTURES FOR OBJECTIVE AND SUBJECTIVE COORDINATION

Coordination in multi-agented systems (MAS) can be conceived as either an agent activity (the subjective viewpoint) or an activity over agents (the objective viewpoint). The two viewpoints have generated two diverging and often contrasting lines of research, as well as different and noncompatible technologies, however, their integration is mandatory for modeling and engineering complex MAS. In this paper, we explore the issue of integration at both the model and the technology levels.

First, by taking FIPA agents and coordination artifacts as reference notions for subjective and objective approaches, respectively, we sketch a framework where agent interactions with coordination artifacts are modeled as physical acts, deliberated and executed by agents analogously to communicative actions. Then, we show how the JADE infrastructure for FIPA-compliant agents, and the TuCSoN infrastructure providing agents with coordination artifacts can be integrated at the technology level, allowing JADE agents to access TuCSoN tuple centers through JADE services.     

Control mechanisms and local perception to support autonomous behavior in virtual animated agents

We propose basic mechanisms that can be used as support to perform computer animated agents with autonomous behavior. We provide the agents with local perception and use a control theory approach, dealing with dynamics and kinematics issues, in order to establish a well structured way to control the agent resources. While maintaining the virtual agents with physical specifications and constraints necessary for animation purposes, the mechanisms provide other realistic needs necessary for providing autonomous behavior. In this way, agents can interact with their environment independent of user interaction, learning the characteristics of its habitat and adapting to it in order to survive. We validate the mechanisms by presenting two platforms with different structures (sensors, actuators, and dynamics) which have used them. As practical results, by using the same control structure, the animated agents are able to perform different tasks like learning attention control and pattern categorization based on multi-modal sensory information, learning how to progress onto a rough terrain, and learning how to perform visual monitoring tasks of their environment.     

A Constraint-Based Reasoning Framework for Behavioural Animation

Behaviour is a reflection of a reasoning process that must deal with constraints imposed by an external environment, internal knowledge and physical structure. This paper proposes a framework for behavioural animation that is based on the next generation of object-oriented, constraint-based expert systems technology, and applies a control structure of knowledge agents and knowledge units to determine the behaviour of objects to be animated. Knowledge agents are responsible for planning, plan implementation and information extraction from the environment. The activity of an agent is dependent on the knowledge units ascribed to them by the animator. The interaction between agents and knowledge units is resolved by the reasoning engine, and thus, influences the eventual motion displayed. An example given is NSAIL, a pilot implementation using the model-based ECHIDNA constraint logic programming shell. With this approach, the motion for a sailing scenario and other behavioural domains can be specified at a high level through the characterization of the knowledge agents.     

Argumentation-Based Agent Interaction in an Ambient-Intelligence Context

A multiagent system uses argumentation-based interaction in an ambient-intelligence context to provide services for people with different combinations of impairments. This paper focuses on ambient intelligence system of agents for knowledge-based and integrated services for mobility-impaired users integrated projectpsilas (ASK-ITIP) furthered the challenge by aiming to support users having different types and combinations of impairments. ASK-ITIP use of argumentation to model a distributed decision-making process for a coalition of assistant agents, each an expert on a different impairment. When a user suffers from a combination of impairments, these agents engage in an argumentation-based dialogue to agree on the user's needs. We found that applying argumentation was natural in this context because, generally speaking, we can abstractly define argumentation as the principled interaction of different, potentially conflicting arguments to obtain a consistent conclusion. Moreover, argumentation-based interaction is combined with a standardized interaction type based on the foundation for intelligent physical agents interaction protocol.     

Independent agents in a globalized world modelled by tissue P systems

For modelling the interactions of independent agents (only interacting via a common environment, but not depending on any direct physical interactions with other agents) in the globalized world, we here consider so-called agent tissue P systems (ATP systems). Based on the model of tissue P systems, such ATP systems consist of cells (independent agents) with specific programs which allow for changing the objects inside the agent or for exchanging objects from inside the agent with objects from the environment through the cell membrane. We investigate the computational power of specific variants of ATP systems, and also discuss the special decidability problem whether or not a given ATP system of a specific type from its initial contents can ever reach a configuration where all objects in the system are contained in a specific subset of the set of objects.     

Integrating BDI Agents with Agent-Based Simulation Platforms

Agent-based models (ABMs) are increasingly being used for exploring and supporting decision making about social science scenarios involving modelling of human agents. However existing agent-based simulation platforms (e.g., SWARM, Repast) provide limited support for the simulation of more complex cognitive agents required by such scenarios. We present a framework that allows Belief-Desire-Intention (BDI) cognitive agents to be embedded in an ABM system. Architecturally, this means that the “brains” of an agent can be modelled in the BDI system in the usual way, while the “body” exists in the ABM system. The architecture is flexible in that the ABM can still have non-BDI agents in the simulation, and the BDI-side can have agents that do not have a physical counterpart (such as an organisation). The framework addresses a key integration challenge of coupling event-based BDI systems, with time-stepped ABM systems. Our framework is modular and supports integration of off-the-shelf BDI systems with off-the-shelf ABM systems. The framework is Open Source, and all integrations and applications are available for use by the modelling community.