Some active governments and their action languages

2019 ◽  
pp. 84-114
Keyword(s):  
2015 ◽  
Vol 16 (2) ◽  
pp. 189-235 ◽  
Author(s):  
DANIELA INCLEZAN ◽  
MICHAEL GELFOND

AbstractThe paper introduces a new modular action language,${\mathcal ALM}$, and illustrates the methodology of its use. It is based on the approach of Gelfond and Lifschitz (1993,Journal of Logic Programming 17, 2–4, 301–321; 1998,Electronic Transactions on AI 3, 16, 193–210) in which a high-level action language is used as a front end for a logic programming system description. The resulting logic programming representation is used to perform various computational tasks. The methodology based on existing action languages works well for small and even medium size systems, but is not meant to deal with larger systems that requirestructuring of knowledge.$\mathcal{ALM}$is meant to remedy this problem. Structuring of knowledge in${\mathcal ALM}$is supported by the concepts ofmodule(a formal description of a specific piece of knowledge packaged as a unit),module hierarchy, andlibrary, and by the division of a system description of${\mathcal ALM}$into two parts:theoryandstructure. Atheoryconsists of one or more modules with a common theme, possibly organized into a module hierarchy based on adependency relation. It contains declarations of sorts, attributes, and properties of the domain together with axioms describing them.Structuresare used to describe the domain's objects. These features, together with the means for defining classes of a domain as special cases of previously defined ones, facilitate the stepwise development, testing, and readability of a knowledge base, as well as the creation of knowledge representation libraries.


2015 ◽  
Vol 30 (4) ◽  
pp. 899-922 ◽  
Author(s):  
Joseph Babb ◽  
Joohyung Lee

Abstract Action languages are formal models of parts of natural language that are designed to describe effects of actions. Many of these languages can be viewed as high-level notations of answer set programs structured to represent transition systems. However, the form of answer set programs considered in the earlier work is quite limited in comparison with the modern Answer Set Programming (ASP) language, which allows several useful constructs for knowledge representation, such as choice rules, aggregates and abstract constraint atoms. We propose a new action language called BC +, which closes the gap between action languages and the modern ASP language. The main idea is to define the semantics of BC + in terms of general stable model semantics for propositional formulas, under which many modern ASP language constructs can be identified with shorthands for propositional formulas. Language BC  + turns out to be sufficiently expressive to encompass the best features of other action languages, such as languages B , C , C + and BC . Computational methods available in ASP solvers are readily applicable to compute BC +, which led to an implementation of the language by extending system cplus2asp .


Author(s):  
Thomas Eiter ◽  
Wolfgang Faber ◽  
Gerald Pfeifer

This chapter introduces planning and knowledge representation in the declarative action language K. Rooted in the area of Knowledge Representation & Reasoning, action languages like K allow the formalization of complex planning problems involving non-determinism and incomplete knowledge in a very flexible manner. By giving an overview of existing planning languages and comparing these against our language, we aim on further promoting the applicability and usefulness of high-level action languages in the area of planning. As opposed to previously existing languages for modeling actions and change, K adopts a logic programming view where fluents representing the epistemic state of an agent might be true, false or undefined in each state. We will show that this view of knowledge states can be fruitfully applied to several well-known planning domains from the literature as well as novel planning domains. Remarkably, K often allows to model problems more concisely than previous action languages. All the examples given can be tested in an available implementation, the DLVK planning system.


2017 ◽  
Vol 17 (5-6) ◽  
pp. 924-941 ◽  
Author(s):  
JOOHYUNG LEE ◽  
NIKHIL LONEY ◽  
YUNSONG MENG

AbstractBoth hybrid automata and action languages are formalisms for describing the evolution of dynamic systems. This paper establishes a formal relationship between them. We show how to succinctly represent hybrid automata in an action language which in turn is defined as a high-level notation for answer set programming modulo theories—an extension of answer set programs to the first-order level similar to the way satisfiability modulo theories (SMT) extends propositional satisfiability (SAT). We first show how to represent linear hybrid automata with convex invariants by an action language modulo theories. A further translation into SMT allows for computing them using SMT solvers that support arithmetic over reals. Next, we extend the representation to the general class of non-linear hybrid automata allowing even non-convex invariants. We represent them by an action language modulo ordinary differential equations, which can be compiled into satisfiability modulo ordinary differential equations. We present a prototype systemcplus2aspmtbased on these translations, which allows for a succinct representation of hybrid transition systems that can be computed effectively by the state-of-the-art SMT solverdReal.


2016 ◽  
Vol 21 (70) ◽  
Author(s):  
Peter Kevin Spink

<p><em>Este artigo parte da observação feita por autores envolvidos com diferentes aspectos das ações públicas, uma vez que o Estado não é sinônimo de assuntos públicos.  Do ponto de vista policêntrico, no qual o público ou públicos são atores-chave e independentes, questiona-se o papel central que a política pública supostamente assumiu na articulação da discussão e provisão de bens e serviços públicos. O artigo adota uma perspectiva histórica da emergência da política pública na língua inglesa em diferentes momentos e focaliza três períodos reconhecidos como aqueles nos quais as democracias anglófonas deram passos significativos para a ampliação da agenda de debate dos assuntos públicos: o New Deal de Roosevelt, 1933; o Governo do Partido Trabalhista britânico, 1945, e as administrações Johnson (1963-1968). Em todos esses casos, houve inovações muito práticas no tratamento de questões muito difíceis, mas com muito pouca – se houve – discussão de política pública. Considerando que fala e ação andam juntas, quais outras linguagens sociais (para usar o termo de Bakhtin, 1986) estavam disponíveis? Ao apontar que elas eram muitas, das quais a maior parte continua presente e bastante ativa hoje, o artigo questiona a centralidade e inevitabilidade da política pública e propõe abordar linguagens de ação pública para o estudo dos assuntos públicos. </em></p>


2019 ◽  
Vol 19 (5-6) ◽  
pp. 1090-1106
Author(s):  
YI WANG ◽  
SHIQI ZHANG ◽  
JOOHYUNG LEE

AbstractTo be responsive to dynamically changing real-world environments, an intelligent agent needs to perform complex sequential decision-making tasks that are often guided by commonsense knowledge. The previous work on this line of research led to the framework called interleaved commonsense reasoning and probabilistic planning (icorpp), which used P-log for representing commmonsense knowledge and Markov Decision Processes (MDPs) or Partially Observable MDPs (POMDPs) for planning under uncertainty. A main limitation of icorpp is that its implementation requires non-trivial engineering efforts to bridge the commonsense reasoning and probabilistic planning formalisms. In this paper, we present a unified framework to integrate icorpp’s reasoning and planning components. In particular, we extend probabilistic action language pBC+ to express utility, belief states, and observation as in POMDP models. Inheriting the advantages of action languages, the new action language provides an elaboration tolerant representation of POMDP that reflects commonsense knowledge. The idea led to the design of the system pbcplus2pomdp, which compiles a pBC+ action description into a POMDP model that can be directly processed by off-the-shelf POMDP solvers to compute an optimal policy of the pBC+ action description. Our experiments show that it retains the advantages of icorpp while avoiding the manual efforts in bridging the commonsense reasoner and the probabilistic planner.


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