Utilization Pattern of Kisan Credit Card (KCC) in Baghpat district of Uttar Pradesh

The Kisan Credit Card scheme introduced in the year 1998 with the objective of fulfillment of credit requirement of the farmers in hassle-free manner for raising agricultural production. There has been tremendous increase in number of Kisan Credit Cards in the rural areas during the last five years. Keeping the importance of KCC, the present study was an attempt to assess utility of KCC as perceived by the farmers. The present investigation was carried out in Baghpat district of Utter Pradesh state with a sample of 120 farmers. The study revealed that the utilization of Kisan Credit Card (KCC) by the respondents was observed as maximum in the aspect i.e. increase in agricultural produce followed by increase in income, crop production activities, utilization of credit for vegetable production and allied activities and duration of utilizing credit. it was also found that Utilization of KCC was considerable low in the respect of the components as utilization for crop insurance, change in cropping pattern and diversified farming. The study suggests that Contingent planning for adverse climatic condition should be communicated to farmers well in advance. With a view to enhance the adoption of improved crop production technologies among the farmer’s awareness and training programmes should be conducted in the regard.

A General Multi-agent Epistemic Planner Based on Higher-order Belief Change

In recent years, multi-agent epistemic planning has received attention from both dynamic logic and planning communities. Existing implementations of multi-agent epistemic planning are based on compilation into classical planning and suffer from various limitations, such as generating only linear plans, restriction to public actions, and incapability to handle disjunctive beliefs. In this paper, we propose a general representation language for multi-agent epistemic planning where the initial KB and the goal, the preconditions and effects of actions can be arbitrary multi-agent epistemic formulas, and the solution is an action tree branching on sensing results.To support efficient reasoning in the multi-agent KD45 logic, we make use of a normal form called alternative cover disjunctive formula (ACDF). We propose basic revision and update algorithms for ACDF formulas. We also handle static propositional common knowledge, which we call constraints. Based on our reasoning, revision and update algorithms, adapting the PrAO algorithm for contingent planning from the literature, we implemented a multi-agent epistemic planner called MAEP. Our experimental results show the viability of our approach.