Ari Saptawijaya

Moral reasoning under uncertainty

We present a Logic Programming framework for moral reasoning under uncertainty. It is enacted by a coherent combination of our two previously implemented systems, Evolution Prospection for decision making, and P-log for probabilistic inference. It allows computing available moral judgments via distinct kinds of prior and post preferences. In introducing various aspects of uncertainty into cases of classical trolley problem moral dilemmas, we show how they may appropriately influence moral judgments, allowing decision makers to opt for different choices, and for these to be externally appraised, even when subject to incomplete evidence, as in courts.

Modelling morality with prospective logic

This paper shows how moral decisions can be drawn computationally by using prospective logic programs. These are employed to model moral dilemmas, as they are able to prospectively look ahead at the consequences of hypothetical moral judgments. With this knowledge of consequences, moral rules are then used to decide the appropriate moral judgments. The whole moral reasoning is achieved via a priori constraints and a posteriori preferences on abductive stable models, two features available in prospective logic programming. In this work we model various moral dilemmas taken from the classic trolley problem and employ the principle of double effect as the moral rule. Our experiments show that preferred moral decisions, i.e. those following the principle of double effect, are successfully delivered.

Incremental Tabling for Query-Driven Propagation of Logic Program Updates

We foster a novel implementation technique for logic program updates, which exploits incremental tabling in logic programming – using XSB Prolog to that effect. Propagation of updates of fluents is controlled by initially keeping any fluent updates pending in the database. And, on the initiative of queries, making active just those updates up to the timestamp of an actual query, by performing incremental assertions of the pending ones. These assertions, in turn, automatically trigger system-implemented incremental bottom-up tabling of other fluents (or their negated complements), with respect to a predefined overall upper time limit, in order to avoid runaway iteration. The frame problem can then be dealt with by inspecting a table for the latest time a fluent is known to be assuredly true, i.e., the latest time it is not supervened by its negated complement, relative to the given query time. To do so, we adopt the dual program transformation for defining and helping propagate, also incrementally and bottom-up, the negated complement of a fluent, in order to establish whether a fluent is still true at some time point, or rather if its complement is. The use of incremental tabling in this approach affords us a form of controlled, but automatic, system level truth-maintenance, up to some actual query time. Consequently, propagation of update side-effects need not employ top-down recursion or bottom-up iteration through a logically defined frame axiom, but can be dealt with by the mechanics of the underlying world. Our approach thus reconciles high-level top-down deliberative reasoning about a query, with autonomous low-level bottom-up world reactivity to ongoing updates, and it might be adopted elsewhere for reasoning in logic.

The Potential of Logic Programming as a Computational Tool to Model Morality

We investigate the potential of logic programming (LP) to computationally model morality aspects studied in philosophy and psychology. We do so by identifying three morality aspects that appear in our view amenable to computational modeling by appropriately exploiting LP features: dual-process model (reactive and deliberative) in moral judgment, justification of moral judgments by contractualism, and intention in moral permissibility. The research aims at developing an LP-based system with features needed in modeling moral settings, putting emphasis on modeling these abovementioned morality aspects. We have currently co-developed two essential ingredients of the LP system, i.e., abduction and logic program updates, by exploiting the benefits of tabling features in logic programs. They serve as the basis for our whole system, into which other reasoning facets will be integrated, to model the surmised morality aspects. We exemplify two applications pertaining moral updating and moral reasoning under uncertainty and detail their implementation. Moreover, we touch upon the potential of our ongoing studies of LP-based cognitive features for the emergence of computational morality, in populations of agents enabled with the capacity for intention recognition, commitment, and apology. We conclude with a “message in a bottle” pertaining to this bridging of individual and population computational morality via cognitive abilities.

Towards Modeling Morality Computationally with Logic Programming

We investigate the potential of logic programming (LP) to model morality aspects studied in philosophy and psychology. We do so by identifying three morality aspects that appear in our view amenable to computational modeling by appropriately exploiting LP features: dual-process model (reactive and deliberative) in moral judgments; justification of moral judgments by contractualism; and intention in moral permissibility. The research aims at developing an LP-based system with features needed in modeling moral settings, putting emphasis on modeling these above mentioned morality aspects. We have currently co-developed two essential ingredients of the LP system, i.e., abduction and logic program updates, by exploiting the benefits of tabling features in logic programs. They serve as the basis for our whole system, into which other reasoning facets will be integrated, to model the surmised morality aspects. Moreover, we touch upon the potential of our ongoing studies of LP based cognitive features for the emergence of computational morality, in populations of agents enabled with the capacity for intention recognition, commitment and apology.

PS-LTL for Constraint-Based Security Protocol Analysis

OWL: A Description Logic Based Ontology Language.- Preference Reasoning.- The G12 Project: Mapping Solver Independent Models to Efficient Solutions.- Use of Logic Programming for Complex Business Rules.- A Generator of Efficient Abstract Machine Implementations and Its Application to Emulator Minimization.- On the Relation Between Answer Set and SAT Procedures (or, Between cmodels and smodels).- Towards an Integration of Answer Set and Constraint Solving.- A Comparison of CLP(FD) and ASP Solutions to NP-Complete Problems.- Guard and Continuation Optimization for Occurrence Representations of CHR.- Coordination of Many Agents.- Parallelizing Union-Find in Constraint Handling Rules Using Confluence Analysis.- An Optimised Semantic Web Query Language Implementation in Prolog.- A Distributed and Probabilistic Concurrent Constraint Programming Language.- HYPROLOG: A New Logic Programming Language with Assumptions and Abduction.- Abduction of Linear Arithmetic Constraints.- Towards Implementations for Advanced Equivalence Checking in Answer-Set Programming.- Hybrid Probabilistic Logic Programs with Non-monotonic Negation.- Reducing Inductive Definitions to Propositional Satisfiability.- Symbolic Support Graph: A Space Efficient Data Structure for Incremental Tabled Evaluation.- Dynamic Mixed-Strategy Evaluation of Tabled Logic Programs.- Nondeterminism Analysis of Functional Logic Programs.- Techniques for Scaling Up Analyses Based on Pre-interpretations.- Deductive Multi-valued Model Checking.- Polynomial Interpretations as a Basis for Termination Analysis of Logic Programs.- Testing for Termination with Monotonicity Constraints.- A Well-Founded Semantics with Disjunction.- Semantics of Framed Temporal Logic Programs.- Practical Higher-Order Pattern Unification with On-the-Fly Raising.- Small Proof Witnesses for LF.- A Type System for CHR.- Decision Support for Personalization on Mobile Devices.- A Generic Framework for the Analysis and Specialization of Logic Programs.- The Need for Ancestor Resolution When Answering Queries in Horn Clause Logic.- Modeling Systems in CLP.- A Sufficient Condition for Strong Equivalence Under the Well-Founded Semantics.- IMPACT: Innovative Models for Prolog with Advanced Control and Tabling.- Using CLP to Characterise Linguistic Lattice Boundaries in a Text Mining Process.- Hybridization of Genetic Algorithms and Constraint Propagation for the BACP.- The MYDDAS Project: Using a Deductive Database for Traffic Characterization.- Open World Reasoning in Datalog.- Optimizing Queries for Heterogeneous Information Sources.- Denotational Semantics Using Horn Concurrent Transaction Logic.- Gentra4cp: A Generic Trace Format for Constraint Programming.- Analyses, Optimizations and Extensions of Constraint Handling Rules: Ph.D. Summary.- Formalization and Verification of Interaction Protocols.- -LTL for Constraint-Based Security Protocol Analysis.- Concurrent Methodologies for Global Optimization.- A Temporal Programming Language for Heterogeneous Information Systems.- Nonmonotonic Logic Programs for the Semantic Web.- ICLP 2005 Doctoral Consortium.- Analysis and Optimization of CHR Programs.Several formal approaches have been proposed to analyse security protocols, e.g. (2,7,11,1,6,12). Recently, a great interest has been growing on the use of constraint solving approach. Initially proposed by Millen and Shmatikov (9), this approach allows analysis of a finite number of protocol sessions. Yet, the representation of protocol runs by symbolic traces (as opposed to concrete traces) captures the possibility of having unbounded message space, allowing analysis over an infinite state space. A constraint is defined as a pair consisting of a message M and a set of messages K that represents the intruders knowledge. Millen and Shmatikov present a procedure to solve a set of constraints, i.e. that in each constraint, M can be built from K. When a set of constraints is solved, then a concrete trace representing an attack over the protocol can be extracted. Corin and Etalle (4) has improved the work of Millen and Shmatikov by presenting a more efficient procedure. However, none of these constraint-based systems provide enough flexibility and expresiveness in specifying security properties. For example, to check secrecy an artificial protocol role is added to simulate whether a secret can be learned by an intruder. Authentication cannot also be checked directly. Moreover, only a built-in notion of authentication is implemented by Millen and Shmatikov in his Prolog implementation (10). This problem motivates our current work. A logical formalism is considered to be an appropriate solution to improve the flexibility and expresiveness in specifying security properties. A preliminary attempt to use logic for specifying local security properties in a constraint-based setting has been carried out (3). Inspired by this work and the successful NPATRL (11,8), we currently explores a variant of linear temporal logic (LTL) over finite traces, PS-LTL , standing for pure-past security LTL (5). In contrast to standard LTL, this logic deals only with past events in a trace. In our current work, a protocol is modelled as in previous works (9,4,3), viz. by protocol roles. A protocol role is a sequence of send and receive events, together with status events to indicate, e.g. that a protocol role has completed her protocol run. A scenario is then used to deal with the number of sessions and protocol roles considered in the analysis. Integrating PS-LTL into our constraint solving approach presents a challenge, since we need to develop a sound and complete decision pro- cedure against symbolic traces, instead of concrete traces. Our idea to address this problem is by concretizing symbolic traces incrementally while deciding a formula. Basically, the decision procedure consists of two steps: transform and decide. The former step transforms a PS-LTL

Counterfactuals, Logic Programming and Agent Morality

This paper supplies a computational model, via Logic Programming (LP), of counterfactual reasoning of autonomous agents with application to morality. Counterfactuals are conjectures about what would have happened had an alternative event occurred. The first contribution of the paper is showing how counterfactual reasoning is modeled using LP, benefiting from LP abduction and updating. The approach is inspired by Pearl’s structural causal model of counterfactuals, where causal direction and conditional reasoning are captured by inferential arrows of rules in LP. Herein, LP abduction hypothesizes background conditions from given evidence or observations, whereas LP updating frame these background conditions as a counterfactual’s context, and then imposes causal interventions on the program through defeasible LP rules. The second contribution it to apply counterfactuals to agent morality using this LP-based approach. We demonstrate its potential for specifying and querying moral issues, by examining viewpoints on moral permissibility via classic moral principles and examples taken from the literature. Application results were validated on a prototype implementing the approach on top of an integrated LP abduction and updating system supporting tabling.

Bridging Two Realms of Machine Ethics

Bridging capabilities between the two realms, to wit, the individual and collective, helps understand the emergent ethical behavior of agents in groups, and implements them not just in simulations, but in the world of future robots and their swarms. On the basis of preceding chapters, this chapter considers the bridging of these two realms in machine ethics. Subsequently, we ponder over the teachings of human moral evolution in this regard. A final coda foretells a road to be tread, and portends about ethical machines and us.

Ocean Color Remote Sensing of Atypical Marine Optical Cases

This study investigates how the number of data collected for algorithm development in typical case-1 waters and optically complex cases can affect the remote sensing of ocean color (OC) products. Marine conditions dominated by the colored dissolved organic matter (CDOM) and nonalgal particles are considered. The applied OC inversion schemes are based on multilayer perceptron (MLP) neural nets for data classification and regression. Simulated data for MLP training are generated with a forward OC model. Results show that a disproportion of samples representing different marine optical cases influences the MLP learning and hence also the data product retrieval, mostly in mixed case-1 and CDOM-dominated environments. A postclassification correction is then employed for performance improvements. Methodological developments are presented, acknowledging the coastal water monitoring prioritized by the Copernicus Earth Observation program.

Towards Practical Tabled Abduction in Logic Programs

Despite its potential as a reasoning paradigm in AI applications, abduction has been on the back burner in logic programming, as abduction can be too difficult to implement, and costly to perform, in particular if abductive solutions are not tabled. If they become tabled, then abductive solutions can be reused, even from one abductive context to another. On the other hand, current Prolog systems, with their tabling mechanisms, are mature enough to facilitate the introduction of tabling abductive solutions (tabled abduction) into them. The concept of tabled abduction has been realized recently in an abductive logic programming system tabdual. Besides tabling abductive solutions, tabdual also relies on the dual transformation. In this paper, we emphasize two tabdual improvements: (1) the dual transformation by need, and (2) a new construct for accessing ongoing abductive solutions, that permits modular mixes between abductive and non-abductive program parts. We apply subsequently these improvements on two distinct problems, and evaluate the performance and the scalability of tabdual on several benchmarks on the basis of these problems, by examining four tabdual variants.