The goal of serving and delighting customers in a personal and near human like manner is very high on automation agendas of most Enterprises. Last few years, have seen huge progress in Natural Language Processing domain which has led to deployments of conversational agents in many enterprises. Most of the current industrial deployments tend to use Monolithic Single Agent designs that model the entire knowledge and skill of the Domain. While this approach is one of the fastest to market, the monolithic design makes it very hard to scale beyond a point. There are also challenges in seamlessly leveraging many tools offered by sub fields of Natural Language Processing and Information Retrieval in a single solution. The sub fields that can be leveraged to provide relevant information are, Question and Answer system, Abstractive Summarization, Semantic Search, Knowledge Graph etc. Current deployments also tend to be very dependent on the underlying Conversational AI platform (open source or commercial) , which is a challenge as this is a fast evolving space and no one platform can be considered future proof even in medium term of 3-4 years. Lately,there is also work done to build multi agent solutions that tend to leverage a concept of master agent. While this has shown promise, this approach still makes the master agent in itself difficult to scale. To address these challenges, we introduce LPar, a distributed multi agent platform for large scale industrial deployment of polyglot, diverse and inter-operable agents. The asynchronous design of LPar supports dynamically expandable domain. We also introduce multiple strategies available in the LPar system to elect the most suitable agent to service a customer query.

中文翻译：

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LPar——用于构建多语言、全通道和工业级自然语言界面的分布式多代理平台

在大多数企业的自动化议程中，以人性化和接近人类的方式服务和取悦客户的目标非常高。过去几年，自然语言处理领域取得了巨大进步，这导致许多企业部署了会话代理。当前的大多数工业部署倾向于使用对域的整个知识和技能进行建模的单片单代理设计。虽然这种方法是上市速度最快的方法之一，但整体设计使其很难扩展到一个点之外。在单个解决方案中无缝利用自然语言处理和信息检索子领域提供的许多工具也存在挑战。可用于提供相关信息的子字段是问答系统、抽象摘要、语义搜索、知识图谱等。当前的部署也往往非常依赖底层的对话 AI 平台（开源或商业），这是一个挑战，因为这是一个快速发展的空间，即使在中期3-4年。最近，也有人致力于构建倾向于利用主代理概念的多代理解决方案。虽然这已经显示出希望，但这种方法仍然使主代理本身难以扩展。为了应对这些挑战，我们引入了 LPar，这是一个分布式多代理平台，用于大规模工业部署多语言、多样化和可互操作的代理。LPar 的异步设计支持动态可扩展的域。