A CHR-based Implementation of Known Arc-Consistency

In classical CLP(FD) systems, domains of variables are completely known at the beginning of the constraint propagation process. However, in systems interacting with an external environment, acquiring the whole domains of variables before the beginning of constraint propagation may cause waste of computation time, or even obsolescence of the acquired data at the time of use. For such cases, the Interactive Constraint Satisfaction Problem (ICSP) model has been proposed as an extension of the CSP model, to make it possible to start constraint propagation even when domains are not fully known, performing acquisition of domain elements only when necessary, and without the need for restarting the propagation after every acquisition. In this paper, we show how a solver for the two sorted CLP language, defined in previous work, to express ICSPs, has been implemented in the Constraint Handling Rules (CHR) language, a declarative language particularly suitable for high level implementation of constraint solvers.Comment: 22 pages, 2 figures, 1 table To appear in Theory and Practice of Logic Programming (TPLP

Learning Max-CSPs via Active Constraint Acquisition

Constraint acquisition can assist non-expert users to model their problems as constraint networks. In active constraint acquisition, this is achieved through an interaction between the learner, who posts examples, and the user who classifies them as solutions or not. Although there has been recent progress in active constraint acquisition, the focus has only been on learning satisfaction problems with hard constraints. In this paper, we deal with the problem of learning soft constraints in optimization problems via active constraint acquisition, specifically in the context of the Max-CSP. Towards this, we first introduce a new type of queries in the context of constraint acquisition, namely partial preference queries, and then we present a novel algorithm for learning soft constraints in Max-CSPs, using such queries. We also give some experimental results

Innovation and Information Acquisition Under Time Inconsistency and Uncertainty

We propose to analyse the hyperbolic discounting preferences effect on the innovator's research investment decision. Investing in research allows him to acquire information, and then to reduce the uncertainty of the risks of his project. We find that whatever the innovator's preferences, that is hyperbolic or time-consistent, there exists a research investment constraint that limits the information acquisition. However, even if the information is free, while a time-consistent agent always acquires information, a hyperbolic agent may prefer staying ignorant. We also emphasize that hyperbolic discounting preferences induce and information precision constraint that leads the hyperbolic innovator to ignore the information whilethe time-consistent innovator gets it. Moreover, the possibility that the agent has a commitment power in the future strengthens this ignorance strategy. Finally, we investigate the impact of existing liability rules on the innovator's decision to acquire information.Innovation, information acquisition, uncertainty, self-control, time inconsistency, liability rules

Towards Reform of Land Acquisition Framework in India

We bring out the fundamental and more important problems with the current framework of land acquisition in India, regulations on land and the functioning of land markets. We argue that reform is overdue and the current framework would be unsustainable in a democracy that is India. Current land prices are highly distorted owing largely to regulatory constraints and the process of takings. Land acquisition more than any other factor is the most important constraint on development and especially in infrastructure development. We bring out the core elements of the reform – the need to define “public purpose” ex-ante for compulsory acquisition of land, the measures that would allow the market price of land to play its correct role, and the approach to valuation. We also argue for an independent valuer when compulsory taking is involved and methods of valuation to ensure that the land owner including the farmer gets the correct value for this land in both compulsory acquisition and in voluntary sale. We also argue the need for a parallel non-compulsory framework for acquisition and develop the key elements of the same. We also bring out alternatives to physical acquisition of land especially in the context of infrastructure development in central places.

Coded spread spectrum digital transmission system design study

Results are presented of a comprehensive study of the performance of Viterbi-decoded convolutional codes in the presence of nonideal carrier tracking and bit synchronization. A constraint length 7, rate 1/3 convolutional code and parameters suitable for the space shuttle coded communications links are used. Mathematical models are developed and theoretical and simulation results are obtained to determine the tracking and acquisition performance of the system. Pseudorandom sequence spread spectrum techniques are also considered to minimize potential degradation caused by multipath

Feature Selection with Cost Constraint

When acquiring consumer data for marketing or new business initiatives, it is important to decide what features of potential customers should be acquired. We study feature selection and acquisition problem with cost constraint in the context of regression prediction. We formulate the feature selection and acquisition problem as a nonlinear programming problem that minimizes prediction error and number of features used in the model subject to a budget constraint. We derive the analytical properties of the solution for this problem and provide a computational procedure for solving the problem. The results of a preliminary experiment demonstrate the effectiveness of our approach