US 8,137,199 B2 · Partitioned artificial intelligence for networked games

Abstract

Partitioned artificial intelligence (AI) for networked gaming. An exemplary system splits the AI into a computationally lightweight server-side component and a computationally intensive client-side component to harness the aggregate computational power of numerous gaming clients. Aggregating resources of many, even thousands of client machines enhances game realism in a manner that would be prohibitively expensive on the central server. The system is tolerant of latency between server and clients. Deterministic and stateless client-side components enable rapid handoff, preemptive migration, and replication of the client-side AI to address problems of client failure and game exploitation. The partitioned AI can support tactical gaming navigation, a challenging task to offload because of sensitivity to latency. The tactical navigation AI calculates influence fields partitioned into server-side and client-side components by means of a Taylor-series approximation.

Claims18

Dependent claims

A method implemented on a gaming server device that hosts an online game, the method comprising:

partitioning an artificial intelligence (AI) process for the online game into a tunable server-side AI component and a client-side AI component that provides tuning parameters for the server-side AI component, the server-side AI component being computationally simpler than the client-side AI component;
running the server-side AI component on the gaming server device;
offloading the client-side AI component to a gaming client device of a game player of the online game;
and
receiving tuning parameters from the client-side AI component to tune the server-side AI component, wherein
the tuning parameters are usable by the server-side AI component over multiple game frames;
the server-side AI component is capable of tolerating stale tuning parameters;
the server-side AI component is capable of tolerating no reception of any tuning parameters for an extended interval of time;
and
the server-side AI component includes a fallback mode in which the server-side AI component operates without input of any tuning parameters from the client-side AI component.

7 more elements

A system implemented on a gaming server device, the system comprising:

a tunable server-side artificial intelligence (AI) component associated with the gaming server device to determine gaming character behaviors from an aggregate vector field representing gaming character positions and influences;
a complementary client-side AI component to intensively compute complex behavior possibilities of a local subset of gaming characters, the complementary client-side AI component being configured to be offloaded to a gaming client device;
wherein the server-side AI component non-intensively computes Taylor-series approximations and sums of influence fields to obtain the aggregate vector field;
wherein the client-side AI component intensively computes tuning parameters for tuning the Taylor-series approximations at the server-side AI component, the tuning parameters comprising coefficients representing the complex behavior possibilities;
and
wherein the server-side AI component solicits the coefficients as advice from the client-side AI component by sending a glimpse of part of a game state to the gaming client device that runs the client-side AI component.

3 more elements

Dependencies are inferred from the claim text.

Partitioned artificial intelligence for networked games

Life of this patent

Partitioned artificial intelligence for networked games

Life of this patent

Abstract

Claims18