Toward Constraint Compliant Goal Formulation and Planning
One part of complying with norms, rules, and preferences is incorporating constraints (such as knowledge of ethics) into one's goal formulation and planning processing. We explore in a simple domain how the encoding of knowledge in different ethical frameworks influences an agent's goal formulation and planning processing and demonstrate ability of an agent to satisfy and satisfice when its collection of relevant constraints includes a mix of "hard" and "soft" constraints of various types. How the agent attempts to comply with ethical constraints depends on the ethical framing and we investigate tradeoffs between deontological framing and utilitarian framing for complying with an ethical norm. Representative scenarios highlight how performing the same task with different framings of the same norm leads to different behaviors. Our explorations suggest an important role for metacognitive judgments in resolving ethical conflicts during goal formulation and planning.
Code (0)
등록된 구현이 없습니다.
Tasks
EthicsSimilar Papers 제목 키워드 기반
Double-Ended Synthesis Planning with Goal-Constrained Bidirectional Search
Computer-aided synthesis planning (CASP) algorithms have demonstrated expert-level abilities in planning retrosynthetic routes to molecules of low to moderate complexity. However, current search methods assume the suffic…
RetrosynthesisvalidSignal Temporal Logic Compliant Co-design of Planning and Control
This work presents a novel co-design strategy that integrates trajectory planning and control to handle STL-based tasks in autonomous robots. The method consists of two phases: $(i)$ learning spatio-temporal motion primi…
Reinforcement LearningTrajectory PlanningMotion PlanningPDPTW-DB: MILP-Based Offline Route Planning for PDPTW with Driver Breaks
The Pickup and Delivery Problem with Time Windows (PDPTW) involves optimizing routes for vehicles to meet pickup and delivery requests within specific time constraints, a challenge commonly faced in logistics and transpo…
SchedulingTwoStep: Multi-agent Task Planning using Classical Planners and Large Language Models
Classical planning formulations like the Planning Domain Definition Language (PDDL) admit action sequences guaranteed to achieve a goal state given an initial state if any are possible. However, reasoning problems define…
Task PlanningGraph Representation Learning for Energy Demand Data: Application to Joint Energy System Planning under Emissions Constraints
A rapid transformation of current electric power and natural gas (NG) infrastructure is imperative to meet the mid-century goal of CO2 emissions reduction requires. This necessitates a long-term planning of the joint pow…
Graph Representation LearningRepresentation Learning