Eva is a multimodal conversational system that helps users to accomplish their domain goals through collaborative dialogue. The system does this by inferring users' intentions and plans to achieve those goals, detects whether obstacles are present, finds plans to overcome them or to achieve higher-level goals, and plans its actions, including speech acts,to help users accomplish those goals. In doing so, the system maintains and reasons with its own beliefs, goals and intentions, and explicitly reasons about those of its user. Belief reasoning is accomplished with a modal Horn-clause meta-interpreter. The planning and reasoning subsystems obey the principles of persistent goals and intentions, including the formation and decomposition of intentions to perform complex actions, as well as the conditions under which they can be given up. In virtue of its planning process, the system treats its speech acts just like its other actions -- physical acts affect physical states, digital acts affect digital states, and speech acts affect mental and social states. This general approach enables Eva to plan a variety of speech acts including requests, informs, questions, confirmations, recommendations, offers, acceptances, greetings, and emotive expressions. Each of these has a formally specified semantics which is used during the planning and reasoning processes. Because it can keep track of different users' mental states, it can engage in multi-party dialogues. Importantly, Eva can explain its utterances because it has created a plan standing behind each of them. Finally, Eva employs multimodal input and output, driving an avatar that can perceive and employ facial and head movements along with emotive speech acts.

翻译：Eva是一个多模态对话系统，通过协作对话帮助用户完成领域目标。该系统通过推断用户意图与实现目标的规划，检测是否存在障碍，寻找克服障碍或达成更高层目标的方案，并规划自身行为（包括言语行为）以协助用户实现目标。在此过程中，系统维护并推理自身的信念、目标和意图，同时显式地推理用户的相应状态。信念推理通过模态霍恩子句元解释器实现。规划与推理子系统遵循持续目标和意图原则，包括执行复杂动作的意图形成与分解机制，以及意图可被放弃的条件。凭借其规划过程，系统将言语行为与其他行为同等对待——物理行为影响物理状态，数字行为影响数字状态，而言语行为影响心理与社会状态。该通用方法使Eva能够规划包括请求、告知、提问、确认、推荐、提议、接受、问候及情感表达在内的多种言语行为。每种言语行为均具有形式化语义规范，这些规范在规划与推理过程中被使用。由于能追踪不同用户的心理状态，系统可参与多方对话。值得强调，Eva之所以能解释其话语，是因为每个话语背后都有相应规划支持。最后，Eva采用多模态输入输出，驱动一个能够感知并运用面部表情、头部动作以及情感言语行为的虚拟化身。