A Temporal Trace Language for Formal Modelling and Analysis of Agent Systems

Sharpanskykh, Alexei; Treur, Jan

doi:10.1007/978-1-4419-6984-2_11

Cited by 26 publications

(28 citation statements)

References 31 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The language TTL (for Temporal Trace Language), described in [2,18], has been adopted for the specification of behavior in organizational models; for more formal details on TTL, see Box 1. To model direct causal or temporal dependencies between two state properties, not the expressive language TTL, but the simpler leads to format is used.…”

Section: Fig 2 and Tree Of Behavioral Propertiesmentioning

confidence: 99%

Illustrating the Contrasting Roles of Self-Organization in Biological Systems with Two Case Histories of Collective Decision Making in the Honey Bee

Johnson¹

2014

In Silico Bees

View full text Add to dashboard Cite

Abstract.One of the unique features of the organization in honeybee societies is the ability to adapt to environmental circumstances in a highly decentralized way. This adaptation takes the form of changes in the allocation of bees to roles, whereby bees individually decide to take up certain roles that require attention. Within the domain of computational modeling of multi-agent systems a trend has developed to model such systems from an organizational perspective. Usually this is done by describing multi-agent systems as organizations using structural elements such as roles and groups, and behavioral properties of these elements: for example, expressions for role behavior, specifying how agents should behave once they fulfill a certain role. In dynamic environments, changes in environmental circumstances may require changes in such organizations as well. In this paper, the change process as seen in honeybee colonies has been modeled by means of techniques from the domain of multi-agent organizations. This results in an adaptive multi-agent organizational model that is able to cope with changing environmental circumstances.

show abstract

Section: Fig 2 and Tree Of Behavioral Propertiesmentioning

confidence: 99%

Illustrating the Contrasting Roles of Self-Organization in Biological Systems with Two Case Histories of Collective Decision Making in the Honey Bee

Johnson¹

2014

In Silico Bees

View full text Add to dashboard Cite

show abstract

“…Verification time is polynomial in the number of isolated time range variables occurring in the formula under verification. For more details, see [14] and [51]. In a real-world context an important part of a validation process is tuning of the model's parameters to a situation at hand, for example, a person's characteristics.…”

Section: About Verification and Validation Using Ttlmentioning

confidence: 99%

Methods for model-based reasoning within agent-based Ambient Intelligence applications

Bosse

Both

Gerritsen

et al. 2012

Knowledge-Based Systems

View full text Add to dashboard Cite

Abstract. Within agent-based Ambient Intelligence applications agents react to humans based on information obtained by sensoring and their knowledge about human functioning. Appropriate types of reactions depend on the extent to which an agent understands the human and is able to interpret the available information (which is often incomplete, and hence multi-interpretable) in order to create a more complete internal image of the environment, including humans. Such an understanding requires that the agent has knowledge to a certain depth about the human"s physiological and mental processes in the form of an explicitly represented model of the causal and dynamic relations describing these processes. In addition, given such a model representation, the agent needs reasoning methods to derive conclusions from the model and interpret the (partial) information available by sensoring. This paper presents the development of a toolbox that can be used by a modeller to design Ambient Intelligence applications. This toolbox contains a number of model-based reasoning methods and approaches to control such reasoning methods. Formal specifications in an executable temporal format are offered, which allows for simulation of reasoning processes and automated verification of the resulting reasoning traces in a dedicated software environment. A number of such simulation experiments and their formal analysis are described. The main contribution of this paper is that the reasoning methods in the toolbox have the possibility to reason using both quantitative and qualitative aspects in combination with a temporal dimension, and the possibility to perform focused reasoning based upon certain heuristic information.

show abstract

“…(Jonker and Treur, 2002;Bosse, Jonker, Meij, Sharpanskykh and Treur, 2009;Sharpanskykh and Treur, 2010).…”

Section: Formalising Patterns In World Dynamics and Their Relationshipsmentioning

confidence: 99%

“…The language is briefly introduced here. For more details, including its semantics, see (Bosse, Jonker, Meij, Sharpanskykh and Treur, 2009;Sharpanskykh and Treur, 2010) 1 . Moreover, to express properties (second-order patterns), that have the form of relationships between the occurrence of patterns, by second-order dynamic properties, the language MetaTTL is introduced.…”

Section: Formalising Patterns In World Dynamics and Their Relationshipsmentioning

confidence: 99%

Patterns in World Dynamics Indicating Agency

Bosse

Treur

2011

Lecture Notes in Computer Science

View full text Add to dashboard Cite

In this paper, the question is addressed which patterns in world dynamics are an indication for a conceptualisation of a world's process as an agent. Six criteria are discussed that provide an indication for the world to show a form agency, and allows for suitable agent-based conceptualisation. The criteria take the form of relationships between the occurrence of certain patterns in the world's dynamics, and are expressed as second-order properties of world dynamics. They are formalised in a reified temporal predicate (meta-)logical language and their use is illustrated in a case study, supported by automated support in the form of simulation and verification.

show abstract

A Temporal Trace Language for Formal Modelling and Analysis of Agent Systems

Cited by 26 publications

References 31 publications

Illustrating the Contrasting Roles of Self-Organization in Biological Systems with Two Case Histories of Collective Decision Making in the Honey Bee

Illustrating the Contrasting Roles of Self-Organization in Biological Systems with Two Case Histories of Collective Decision Making in the Honey Bee

Methods for model-based reasoning within agent-based Ambient Intelligence applications

Patterns in World Dynamics Indicating Agency

Contact Info

Product

Resources

About