A method comprising, at a mobile device: determining whether a dynamic user profile is to transition from a first state to a second state based, at least in part, on one or more sensed indicators, wherein said second state comprises a previously unknown state, and said dynamic user profile being indicative of a current inferable user behavior context for a user co-located with said mobile device; transitioning said dynamic user profile from said first state to said second state in response to a determination that said dynamic user profile is to transition from said first state to said second state; and operatively affecting one or more functions performed, at least in part, by said mobile device based, at least in part, on said transition of said dynamic user profile from said first state to said second state; wherein determining whether said dynamic user profile is to transition from said first state to said second state further comprises: determining whether said one or more sensed indicators matches one or more stored patterns or models of behavior previously associated with at least said first state; and in response to a determination that said one or more sensed indicators does not match said one or more stored patterns or models of behavior previously associated with at least said first state, determining that said dynamic user profile is to transition from said first state to said second state; the method further comprising: in response to a determination that said one or more sensed indicators does not match said one or more stored patterns or models of behavior previously associated with at least said first state and responsive to an absence of a match from an attempt to match said one or more sensed indicators with a known or previously observed patterns or models, establishing and learning said previously unknown state based, at least in part, on said one or more sensed indicators. determining whether a dynamic user profile is to transition from a first state to a second state based, at least in part, on one or more sensed indicators, wherein said second state comprises a previously unknown state, and said dynamic user profile being indicative of a current inferable user behavior context for a user co-located with said mobile device; transitioning said dynamic user profile from said first state to said second state in response to a determination that said dynamic user profile is to transition from said first state to said second state; and operatively affecting one or more functions performed, at least in part, by said mobile device based, at least in part, on said transition of said dynamic user profile from said first state to said second state; wherein determining whether said dynamic user profile is to transition from said first state to said second state further comprises: determining whether said one or more sensed indicators matches one or more stored patterns or models of behavior previously associated with at least said first state; and in response to a determination that said one or more sensed indicators does not match said one or more stored patterns or models of behavior previously associated with at least said first state, determining that said dynamic user profile is to transition from said first state to said second state; determining whether said one or more sensed indicators matches one or more stored patterns or models of behavior previously associated with at least said first state; and in response to a determination that said one or more sensed indicators does not match said one or more stored patterns or models of behavior previously associated with at least said first state, determining that said dynamic user profile is to transition from said first state to said second state; the method further comprising: in response to a determination that said one or more sensed indicators does not match said one or more stored patterns or models of behavior previously associated with at least said first state and responsive to an absence of a match from an attempt to match said one or more sensed indicators with a known or previously observed patterns or models, establishing and learning said previously unknown state based, at least in part, on said one or more sensed indicators.