Adult aim chat bot

Generally, one inclines to club many intents to simplify the bot building process.

But, it would only lead to instability as the bot grows.

More intents mean the probability to hit the right intent is less. A good set of general and specific test cases are required to gauge the stability of a bot. Bots, which are considered to be stupid by an average human being will soon stop to exist.

Generic test cases are those common to any bot, it is a good practice to build and use generic test cases. The bot should not repeat itself; it should not ask obvious questions; in some cases, the bot should remember some information even across different sessions. Thus, it is important to match smartness of bots to that of an average human.

Reinforcement learning techniques can be used here to predict the next possible intent, which could be of interest to the user.

Determining the reward to the model would be critical in this approach.

The output of specific test cases can be used to measure the Bot stability. So, follow best practices in building these test cases. There are many ways in which context can is handled.One which is applicable often is intent clustering.In this approach, intents are grouped into clusters which have some common slots.The common slots are named the same across intents.The slots which have the same name within a cluster carry the same value.

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More than two contexts can be handled by asking for clarification from the user.

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