How should a machine intelligence perform unsupervised structure discovery over streams of sensory input? One approach to this problem is to cast it as an apperception task. Here, the task is to construct an explicit interpretable theory that both explains the sensory sequence and also satisfies a set of unity conditions, designed to ensure that the constituents of the theory are connected in a relational structure. However, the original formulation of the apperception task had one fundamental limitation: it assumed the raw sensory input had already been parsed using a set of discrete categories, so that all the system had to do was receive this already-digested symbolic input, and make sense of it. But what if we don't have access to pre-parsed input? What if our sensory sequence is raw unprocessed information? The central contribution of this paper is a neuro-symbolic framework for distilling interpretable theories out of streams of raw, unprocessed sensory experience. First, we extend the definition of the apperception task to include ambiguous (but still symbolic) input: sequences of sets of disjunctions. Next, we use a neural network to map raw sensory input to disjunctive input. Our binary neural network is encoded as a logic program, so the weights of the network and the rules of the theory can be solved jointly as a single SAT problem. This way, we are able to jointly learn how to perceive (mapping raw sensory information to concepts) and apperceive (combining concepts into declarative rules).

How should a machine intelligence perform unsupervised structure discovery over streams of sensory input? One approach to this problem is to cast it as an apperception task [1]. Here, the task is to construct an explicit interpretable theory that both explains the sensory sequence and also satisfies a set of unity conditions, designed to ensure that the constituents of the theory are connected in a relational structure. However, the original formulation of the apperception task had one fundamental limitation: it assumed the raw sensory input had already been parsed using a set of discrete categories, so that all the system had to do was receive this already-digested symbolic input, and make sense of it. But what if we don't have access to pre-parsed input? What if our sensory sequence is raw unprocessed information? The central contribution of this paper is a neuro-symbolic framework for distilling interpretable theories out of streams of raw, unprocessed sensory experience. First, we extend the definition of the apperception task to include ambiguous (but still symbolic) input: sequences of sets of disjunctions. Next, we use a neural network to map raw sensory input to disjunctive input. Our binary neural network is encoded as a logic program, so the weights of the network and the rules of the theory can be solved jointly as a single SAT problem. This way, we are able to jointly learn how to perceive (mapping raw sensory information to concepts) and apperceive (combining concepts into declarative rules).

This paper attempts to answer a central question in unsupervised learning: what does it mean to “make sense” of a sensory sequence? In our formalization, making sense involves constructing a symbolic causal theory that both explains the sensory sequence and also satisfies a set of unity conditions. The unity conditions insist that the constituents of the causal theory – objects, properties, and laws – must be integrated into a coherent whole. On our account, making sense of sensory input is a type of program synthesis, but it is unsupervised program synthesis. Our second contribution is a computer implementation, the Apperception Engine, that was designed to satisfy the above requirements. Our system is able to produce interpretable human-readable causal theories from very small amounts of data, because of the strong inductive bias provided by the unity conditions. A causal theory produced by our system is able to predict future sensor readings, as well as retrodict earlier readings, and impute (fill in the blanks of) missing sensory readings, in any combination. In fact, it is able to do all three tasks simultaneously. We tested the engine in a diverse variety of domains, including cellular automata, rhythms and simple nursery tunes, multi-modal binding problems, occlusion tasks, and sequence induction intelligence tests. In each domain, we test our engine's ability to predict future sensor values, retrodict earlier sensor values, and impute missing sensory data. The Apperception Engine performs well in all these domains, significantly out-performing neural net baselines. We note in particular that in the sequence induction intelligence tests, our system achieved human-level performance. This is notable because our system is not a bespoke system designed specifically to solve intelligence tests, but a general-purpose system that was designed to make sense of any sensory sequence.

Systems for symbolic event recognition accept as input a stream of time-stamped events from sensors and other computational devices, and seek to identify high-level composite events, collections of events that satisfy some pattern. RTEC is an Event Calculus dialect with novel implementation and `windowing' techniques that allow for efficient event recognition, scalable to large data streams. RTEC supports the expression of rather complex events, such as `two people are fighting', using simple primitives. It can operate in the absence of filtering modules, as it is only slightly affected by data that are irrelevant to the events we want to recognise. Furthermore, RTEC can deal with applications where event data arrive with a (variable) delay from, and are revised by, the underlying sources. RTEC can update already recognised events and recognise new events when data arrive with a delay or following data revision. We evaluate RTEC both theoretically, presenting a complexity analysis, and experimentally, using two real-world applications. The evaluation shows that RTEC can support real-time event recognition and is capable of meeting the performance requirements identified in a survey of event processing use cases.

UNLABELLED: microRibonucleic acid (miRNAs) are small regulatory molecules that act by mRNA degradation or via translational repression. Although many miRNAs are ubiquitously expressed, a small subset have differential expression patterns that may give rise to tissue-specific complexes. MOTIVATION: This work studies gene targeting patterns amongst miRNAs with differential expression profiles, and links this to control and regulation of protein complexes. RESULTS: We find that, when a pair of miRNAs are not expressed in the same tissues, there is a higher tendency for them to target the direct partners of the same hub proteins. At the same time, they also avoid targeting the same set of hub-spokes. Moreover, the complexes corresponding to these hub-spokes tend to be specific and nonoverlapping. This suggests that the effect of miRNAs on the formation of complexes is specific.

Electronic markets, dispute resolution and negotiation protocols are three types of application domains that can be viewed as open agent societies. Key characteristics of such societies are agent heterogeneity, conflicting individual goals and unpredictable behavior. Members of such societies may fail to, or even choose not to, conform to the norms governing their interactions. It has been argued that systems of this type should have a formal, declarative, verifiable, and meaningful semantics. We present a theoretical and computational framework being developed for the executable specification of open agent societies. We adopt an external perspective and view societies as instances of normative systems. In this article, we demonstrate how the framework can be applied to specifying and executing a contract-net protocol. The specification is formalized in two action languages, the C + language and the Event Calculus, and executed using respective software implementations, the Causal Calculator and the Society Visualizer. We evaluate our executable specification in the light of the presented case study, discussing the strengths and weaknesses of the employed action languages for the specification of open agent societies.

Despite their widespread adoption, Role-based Access Control (RBAC) models exhibit certain shortcomings that make them less than ideal for deployment in, for example, distributed access control. In the distributed case, standard RBAC assumptions (e.g., of relatively static access policies, managed by human users, with complete information available about users and job functions) do not necessarily apply. Moreover, RBAC is restricted in the sense that it is based on one type of ascribed status, an assignment of a user to a role. In this article, we introduce the status-based access control (SBAC) model for distributed access control. The SBAC model (or family of models) is based on the notion of users having an action status as well as an ascribed status. A user's action status is established, in part, from a history of events that relate to the user; this history enables changing access policy requirements to be naturally accommodated. The approach can be implemented as an autonomous agent that reasons about the events, actions, and a history (of events and actions), which relates to a requester for access to resources, in order to decide whether the requester is permitted the access sought. We define a number of algebras for composing SBAC policies, algebras that exploit the language that we introduce for SBAC policy representation: identification-based logic programs. The SBAC model is richer than RBAC models and the policies that can be represented in our approach are more expressive than the policies admitted by a number of monotonic languages that have been hitherto described for representing distributed access control requirements. Our algebras generalize existing algebras that have been defined for access policy composition. We also describe an approach for the efficient implementation of SBAC policies.

Abstract Summary: SEAN is an application that predicts single nucleotide polymorphisms (SNPs) using multiple sequence alignments produced from expressed sequence tag (EST) clusters. The algorithm uses rules of sequence identity and SNP abundance to determine the quality of the prediction. A Java viewer is provided to display the EST alignments and predicted SNPs. Availability: SEAN is freely available from Contact: [email protected]

MOTIVATION: The output of a bioinformatic tool such as BLAST must usually be interpreted by an expert before reliable conclusions can be drawn. This may be based upon the expert's experience, additional data and statistical analysis. Often the process is laborious, goes unrecorded and may be biased. Argumentation is an established technique for reasoning about situations where absolute truth or precise probability is impossible to determine. RESULTS: We demonstrate the application of argumentation to 3D-PSSM, a protein structure prediction tool. The expert's interpretation of results is represented as an argumentation framework. Given a 3D-PSSM result, an automated procedure constructs arguments for and against the conclusion that the result is a good predictor of protein structure. In addition to capturing the unique expertise of the author of 3D-PSSM for distribution to users, an improvement in recall of 5-10 percentage points is achieved. This technique can be applied to a wide range of bioinformatic tools. AVAILABILITY: Example public server and benchmarking data are available at http://www.sbg.bio.ic.ac.uk/~brj03/argumentation/paper/. Source code available on request.

Voting is an essential element of mechanism design for multi-agent systems, and by extension applications built on such systems, which includes ad hoc networks, virtual organizations, and decision support tools implementing online deliberative assemblies. Much attention has been given both to designing the process so that it is resistant to manipulation by strategic voting and so that an automated system can follow rules of order as developed for the conduct of formal meetings. In this paper, we define, characterize, formally specify and animate a general voting protocol. In particular we show how the requirements established by the characterization are captured by the specification and are exhibited by the animation. The importance of these requirements is in ensuring robustness by respecting the way in which votes are cast and the outcome is declared, especially as this issue relates to the 2004 ACM Statement on E-Voting.

Voting is an essential element of mechanism design for multi-agent systems, and decision support for CSCW tools implementing online deliberative assemblies. Much attention has been given both to designing the process so that it is resistant to manipulation by strategic voting, and so that an automated system can follow rules of order as developed for the conduct of formal meetings. In this paper, we formalise a general voting protocol trying to take into account a right to cast a vote, and an entitlement that the vote cast is counted in the correct way. We discuss the design and development of a system for online deliberative assemblies, that incorporates this protocol as part of a suite of protocols which collectively implement rules of order. We conclude with some comments on the voting protocol as it relates to the 2004 ACM Statement on E-Voting.

In this work, we have been principally concerned with the representation of contracts so that their normative state may be tracked in an automated fashion over their deployment lifetime. The normative state of a contract, at a particular time, is the aggregation of instances of normative relations that hold between contract parties at that time, plus the current values of contract variables. The effects of contract events on the normative state of a contract are specified using an XML formalization of the Event Calculus, called ecXML. We use an example mail service agreement from the domain of web services to ground the discussion of our work. We give a characterization of the agreement according to the normative concepts of obligation, power and permission, and show how the ecXML representation may be used to track the state of the agreement, according to a narrative of contract events. We also give a description of a state tracking architecture, and a contract deployment tool, both of which have been implemented in the course of our work.

Open multi-agent computational systems are composed of heterogeneous and possibly antagonistic software entities. Characteristic features are limited trust and unpredictable behaviour. Members of such systems may fail to, or even choose not to, conform to the norms governing their interactions. It has been argued that systems of this type should have a formal, declarative, verifiable, and meaningful semantics. We present a theoretical and computational framework being developed for the executable specification of such systems. We adopt an external perspective and view open computational systems as instances of normative systems. In this paper we demonstrate how the framework can be applied to specifying and executing an argumentation protocol based on Brewka's reconstruction of Rescher's theory of formal disputation. The specification is formalised in the action language C+ and executed using the 'Causal Calculator' (CCALC) implementation.

The Kanger-Lindahl theory of normative positions attempts to use a combination of deontic logic (the logic of obligation and permission) and a logic of action/agency to give a formal account of obligations, duties, rights, and other complex normative concepts. This paper presents a generalization and further development of this theory, together with methods for its automation and application to practical examples. The resulting theory is intended to be applied in the representation and analysis of laws, regulations, and contracts, in the specification of aspects of computer systems, in multiagent systems, and as a contribution to the formal theory of organizations. Particular attention is paid to representations at varying levels of detail and the relationships that hold between them. The last part presents Norman-G, an automated support system intended to facilitate application of the theory to the analysis of practical problems, with a small example to illustrate its use.

We present an abstract framework for designing and developing globalised interactive systems from simple components viewed as games [1] (K. Stathis, M.J. Sergot, Games as a Metaphor for Interactive Systems, in: M.A. Sasse, R.J. Cunningham, R.L. Winder (Eds.), People and Computers XI (Proceedings of HCI′96), August 1996, London, UK, BCS Conference Series, Springer-Varlag, pp. 19–33). We identify a set of concepts required to specify and implement interactions, in such a way whereby instantiating the specifications and implementations of games we obtain components that correspond to localised instances of an interactive system. Localisation is also obtained by either customising the specification or the implementation of the interactive system, or both. The framework also caters for complex interactive systems which are interpreted as compound games built-up from sub-games. In this case, coordination of sub-games is the main issue that we must address at the global level. This is resolved by specifying and implementing sub-games as active components of the more complex games, and, as a result, we localise the coordination of components in the interactive system. The framework lends itself towards a methodology that is suitable for globalising the development of interactive systems.

We present a general approach for modeling temporal aspects of objects in a logic programming framework. Change is formulated in the context of a database which stores explicitly a record of all changes that have occurred to objects and thus (implicitly) all states of objects in the database. A snapshot of the database at any given time is an object-oriented database, in the sense that it supports an object-based data model. An object is viewed as a collection of simple atomic formulas, with support for an explicit notion of object identity, classes and inheritance. The event calculus is a treatment of time and change in first-order classical logic augmented with negation as failure. The paper develops a variant of the event calculus for representing changes to objects, including change in internal state of objects, creation and deletion of objects, and mutation of objects over time. The concluding sections present two natural and straightforward extensions, to deal with versioning of objects and schema evolution, and a sketch of implementation strategies for practical application to temporal object-oriented databases.

We present an approach for modelling the structure and coarse content of legal documents with a view to providing automated support for the drafting of contracts and contract database retrieval.The approach is designed to be applicable where contract drafting is based on model-form contracts or on existing examples of a similar type.The main features of the approach are: (1) the representation addresses the structure and the interrelationships between the constituent parts of contracts, bu i not the [ext of the document itselfi (2) the representation of documents is separated from the mechanisms that manipulate it; and (3) the drafting process is subject to a collection of explicitly stated constraints that govern the structure of the documents.We describe the representation of document instances and of 'generic Llocuments', which are data structures used to drive the creation of new document instances, and we show extracts from a sample session to illustrate the features of a prototype system implemented in MacProlog,

Article Indian central civil service pension rules: a case study in logic programming applied to regulations Share on Authors: M. J. Sergot Department of Computing, Imperial College of Science, Technology and Medicine, London SW7 2BZ Department of Computing, Imperial College of Science, Technology and Medicine, London SW7 2BZView Profile , A. S. Kamble KBCS Nodal Centre, Department of Electronics, Government of India, New Delhi KBCS Nodal Centre, Department of Electronics, Government of India, New DelhiView Profile , K. K. Bajaj KBCS Nodal Centre, Department of Electronics, Government of India, New Delhi KBCS Nodal Centre, Department of Electronics, Government of India, New DelhiView Profile Authors Info & Claims ICAIL '91: Proceedings of the 3rd international conference on Artificial intelligence and lawMay 1991 Pages 118–127https://doi.org/10.1145/112646.112661Online:01 May 1991Publication History 10citation412DownloadsMetricsTotal Citations10Total Downloads412Last 12 Months14Last 6 weeks1 Get Citation AlertsNew Citation Alert added!This alert has been successfully added and will be sent to:You will be notified whenever a record that you have chosen has been cited.To manage your alert preferences, click on the button below.Manage my AlertsNew Citation Alert!Please log in to your account Save to BinderSave to BinderCreate a New BinderNameCancelCreateExport CitationPublisher SiteGet Access

INTRODUCIIONThe papct describes a project which began in April 1986 on the representation in logic of a large portion of the United Kingdom's welfare law; specifically the legislation relating to 'Supplementary Benefit'.The paper describes the nature of the legislation and the kinds of tasks which the ,epftsentation is intended to support, reports on the progress of the project so far, and describes some of the knowledge representation problems that have arisen and how we propose to overcome them.The principal aim of the paper is to elaborate on our use of logic programming techniques for applications in law, and on our view of how executable logical models of law can be used to support various aspects of legal reasoning.