HLogo: A Parallel Haskell Variant of NetLogo

Bezirgiannis, Nikolaos; Prasetya, I. S. W. B.; Sakellariou, Ilias

doi:10.5220/0005983501190128

Cited by 3 publications

(6 citation statements)

References 29 publications

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“…This paper extends our previous work reported in [4] by introducing in greater depth a new ABMS framework called HLogo. The framework is strongly inspired by the well-known NetLogo framework [38].…”

Section: Introductionsupporting

confidence: 65%

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HLogo: A Haskell STM-Based Parallel Variant of NetLogo

Bezirgiannis

Prasetya

Sakellariou

2017

Advances in Intelligent Systems and Computing

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Agent-based Modeling and Simulation (ABMS) has become a quite popular approach among researchers in the community, mainly due to its simplicity, expressiveness and wide applicability. However, in most cases, ABMS tools demonstrate reduced performance, especially when dealing with large experiments. This paper presents HLogo, a parallel variant of the NetLogo ABMS framework, that aims to increase the performance of simulations by utilizing Software Transactional Memory and multi-core CPUs, while maintaining the user friendliness of NetLogo. HLogo is implemented as a Domain Specific Language embedded in the functional language Haskell, which means that it also inherits Haskell's features, such as strong static typing, a module system and a vast collection of programming libraries.

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Section: Introductionsupporting

confidence: 65%

“…Some important features of Haskell, the implementation language of choice, are presented in Sect. 4. The HLogo language is presented in Sect.…”

Section: Introductionmentioning

confidence: 99%

HLogo: A Haskell STM-Based Parallel Variant of NetLogo

Bezirgiannis

Prasetya

Sakellariou

2017

Advances in Intelligent Systems and Computing

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“…Example. Figure 3 shows a scene in a game called Lab Recruits 7 . Imagine that we want to test that the door (white circled) works (it can be opened).…”

Section: Agent Belief and Goalmentioning

confidence: 99%

“…To program agents, without having to do everything from scratch, we can either use an agent 'framework', which essentially provides a library, or we use a dedicated agent programming language. Examples of agent frameworks are JADE [6] and aplib for Java, HLogo [7] for Haskell, and PROFETA [18] for Python. Examples of dedicated agent languages are JASON [8], 2APL [9], GOAL [24], JADEL [25], and SARL [39].…”

Section: Related Workmentioning

confidence: 99%

Aplib: Tactical Agents for Testing Computer Games

Prasetya

Dastani

Prada

et al. 2020

Engineering Multi-Agent Systems

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Modern interactive software, such as computer games, employ complex user interfaces. Although these user interfaces make the games attractive and powerful, unfortunately they also make them extremely difficult to test. Not only do we have to deal with their functional complexity, but also the fine grained interactivity of their user interface blows up their interaction space, so that traditional automated testing techniques have trouble handling it. An agent-based testing approach offers an alternative solution: agents' goal driven planning, adaptivity, and reasoning ability can provide an extra edge towards effective navigation in complex interaction space. This paper presents aplib, a Java library for programming intelligent test agents, featuring novel tactical programming as an abstract way to exert control over agents' underlying reasoning-based behavior. This type of control is suitable for programming testing tasks. Aplib is implemented in such a way to provide the fluency of a Domain Specific Language (DSL). Its embedded DSL approach also means that aplib programmers will get all the advantages that Java programmers get: rich language features and a whole array of development tools.Keywords: automated game testing • AI for automated testing • intelligent agents for testing • agents tactical programming • intelligent agent programming

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“…To program agents, without having to do everything from scratch, we can either use an agent 'framework', which essentially provides a library, or we use a dedicated agent programming language. Examples of agent frameworks are JADE (Bellifemine et al, 1999) for Java, HLogo (Bezirgiannis et al, 2016) for Haskell, and PROFETA (Fichera et al, 2017) for Python. Examples of dedicated agent languages are JASON (Bordini et al, 2007), 2APL (Dastani, 2008), GOAL (Hindriks, 2018), JADEL (Iotti, 2018), and SARL (Rodriguez et al, 2014).…”

Section: Related Workmentioning

confidence: 99%

Aplib: Tactical Programming of Intelligent Agents

Prasetya

2019

Preprint

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This paper presents aplib, a Java library for programming intelligent agents, featuring BDI and multi agency, but adding on top of it a novel layer of tactical programming inspired by the domain of theorem proving. Aplib is also implemented in such a way to provide the fluency of a Domain Specific Language (DSL). Compared to dedicated BDI agent programming languages such as JASON, 2APL, or GOAL, aplib's embedded DSL approach does mean that aplib programmers will still be limited by Java syntax, but on other hand they get all the advantages that Java programmers get: rich language features (object orientation, static type checking, λ-expression, libraries, etc), a whole array of development tools, integration with other technologies, large community, etc.1 https://iv4xr-project.github.io/aplib/ 2 With respect to the previously mentioned concept of 'tactic' in LCF theorem provers, aplib tactics express

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HLogo: A Parallel Haskell Variant of NetLogo

Cited by 3 publications

References 29 publications

HLogo: A Haskell STM-Based Parallel Variant of NetLogo

HLogo: A Haskell STM-Based Parallel Variant of NetLogo

Aplib: Tactical Agents for Testing Computer Games

Aplib: Tactical Programming of Intelligent Agents

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